Python2/PyMuPDF: mupdf-source/thirdparty/leptonica/src/convolve.c comparison

comparison mupdf-source/thirdparty/leptonica/src/convolve.c @ 2:b50eed0cc0ef upstream

ADD: MuPDF v1.26.7: the MuPDF source as downloaded by a default build of PyMuPDF 1.26.4. The directory name has changed: no version number in the expanded directory now.

author	Franz Glasner <fzglas.hg@dom66.de>
date	Mon, 15 Sep 2025 11:43:07 +0200
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-:1d09e1dec1d9
+:b50eed0cc0ef
+/*====================================================================*
+-  Copyright (C) 2001 Leptonica.  All rights reserved.
+-
+-  Redistribution and use in source and binary forms, with or without
+-  modification, are permitted provided that the following conditions
+-  are met:
+-  1. Redistributions of source code must retain the above copyright
+-     notice, this list of conditions and the following disclaimer.
+-  2. Redistributions in binary form must reproduce the above
+-     copyright notice, this list of conditions and the following
+-     disclaimer in the documentation and/or other materials
+-     provided with the distribution.
+-
+-  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+-  ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+-  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+-  A PARTICULAR PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL ANY
+-  CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+-  EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+-  PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+-  PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
+-  OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+-  NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+-  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+*====================================================================*/
+/*!
+* \file convolve.c
+* <pre>
+*
+*      Top level grayscale or color block convolution
+*          PIX          *pixBlockconv()
+*
+*      Grayscale block convolution
+*          PIX          *pixBlockconvGray()
+*          static void   blockconvLow()
+*
+*      Accumulator for 1, 8 and 32 bpp convolution
+*          PIX          *pixBlockconvAccum()
+*          static void   blockconvAccumLow()
+*
+*      Un-normalized grayscale block convolution
+*          PIX          *pixBlockconvGrayUnnormalized()
+*
+*      Tiled grayscale or color block convolution
+*          PIX          *pixBlockconvTiled()
+*          PIX          *pixBlockconvGrayTile()
+*
+*      Convolution for mean, mean square, variance and rms deviation
+*      in specified window
+*          l_int32       pixWindowedStats()
+*          PIX          *pixWindowedMean()
+*          PIX          *pixWindowedMeanSquare()
+*          l_int32       pixWindowedVariance()
+*          DPIX         *pixMeanSquareAccum()
+*
+*      Binary block sum and rank filter
+*          PIX          *pixBlockrank()
+*          PIX          *pixBlocksum()
+*          static void   blocksumLow()
+*
+*      Census transform
+*          PIX          *pixCensusTransform()
+*
+*      Generic convolution (with Pix)
+*          PIX          *pixConvolve()
+*          PIX          *pixConvolveSep()
+*          PIX          *pixConvolveRGB()
+*          PIX          *pixConvolveRGBSep()
+*
+*      Generic convolution (with float arrays)
+*          FPIX         *fpixConvolve()
+*          FPIX         *fpixConvolveSep()
+*
+*      Convolution with bias (for non-negative output)
+*          PIX          *pixConvolveWithBias()
+*
+*      Set parameter for convolution subsampling
+*          void          l_setConvolveSampling()
+*
+*      Additive gaussian noise
+*          PIX          *pixAddGaussNoise()
+*          l_float32     gaussDistribSampling()
+* </pre>
+*/
+#ifdef HAVE_CONFIG_H
+#include <config_auto.h>
+#endif  /* HAVE_CONFIG_H */
+#include <math.h>
+#include "allheaders.h"
+/* These globals determine the subsampling factors for
+* generic convolution of pix and fpix.  Declare extern to use.
+* To change the values, use l_setConvolveSampling(). */
+LEPT_DLL l_int32  ConvolveSamplingFactX = 1;
+LEPT_DLL l_int32  ConvolveSamplingFactY = 1;
+/* Low-level static functions */
+static void blockconvLow(l_uint32 *data, l_int32 w, l_int32 h, l_int32 wpl,
+l_uint32 *dataa, l_int32 wpla, l_int32 wc,
+l_int32 hc);
+static void blockconvAccumLow(l_uint32 *datad, l_int32 w, l_int32 h,
+l_int32 wpld, l_uint32 *datas, l_int32 d,
+l_int32 wpls);
+static void blocksumLow(l_uint32 *datad, l_int32 w, l_int32 h, l_int32 wpl,
+l_uint32 *dataa, l_int32 wpla, l_int32 wc, l_int32 hc);
+/*----------------------------------------------------------------------*
+*             Top-level grayscale or color block convolution           *
+*----------------------------------------------------------------------*/
+/*!
+* \brief   pixBlockconv()
+*
+* \param[in]    pix      8 or 32 bpp; or 2, 4 or 8 bpp with colormap
+* \param[in]    wc, hc   half width/height of convolution kernel
+* \return  pixd, or NULL on error
+*
+* <pre>
+* Notes:
+*      (1) The full width and height of the convolution kernel
+*          are (2 * wc + 1) and (2 * hc + 1)
+*      (2) Returns a copy if either wc or hc are 0
+*      (3) Require that w >= 2 * wc + 1 and h >= 2 * hc + 1,
+*          where (w,h) are the dimensions of pixs.  Attempt to
+*          reduce the kernel size if necessary.
+* </pre>
+*/
+PIX  *
+pixBlockconv(PIX     *pix,
+l_int32  wc,
+l_int32  hc)
+{
+l_int32  w, h, d;
+PIX     *pixs, *pixd, *pixr, *pixrc, *pixg, *pixgc, *pixb, *pixbc;
+if (!pix)
+return (PIX *)ERROR_PTR("pix not defined", __func__, NULL);
+if (wc <= 0 || hc <= 0)
+return pixCopy(NULL, pix);
+pixGetDimensions(pix, &w, &h, &d);
+if (w < 2 * wc + 1 || h < 2 * hc + 1) {
+L_WARNING("kernel too large: wc = %d, hc = %d, w = %d, h = %d; "
+"reducing!\n", __func__, wc, hc, w, h);
+wc = L_MIN(wc, (w - 1) / 2);
+hc = L_MIN(hc, (h - 1) / 2);
+}
+if (wc == 0 || hc == 0)   /* no-op */
+return pixCopy(NULL, pix);
+/* Remove colormap if necessary */
+if ((d == 2 || d == 4 || d == 8) && pixGetColormap(pix)) {
+L_WARNING("pix has colormap; removing\n", __func__);
+pixs = pixRemoveColormap(pix, REMOVE_CMAP_BASED_ON_SRC);
+d = pixGetDepth(pixs);
+} else {
+pixs = pixClone(pix);
+}
+if (d != 8 && d != 32) {
+pixDestroy(&pixs);
+return (PIX *)ERROR_PTR("depth not 8 or 32 bpp", __func__, NULL);
+}
+if (d == 8) {
+pixd = pixBlockconvGray(pixs, NULL, wc, hc);
+} else { /* d == 32 */
+pixr = pixGetRGBComponent(pixs, COLOR_RED);
+pixrc = pixBlockconvGray(pixr, NULL, wc, hc);
+pixDestroy(&pixr);
+pixg = pixGetRGBComponent(pixs, COLOR_GREEN);
+pixgc = pixBlockconvGray(pixg, NULL, wc, hc);
+pixDestroy(&pixg);
+pixb = pixGetRGBComponent(pixs, COLOR_BLUE);
+pixbc = pixBlockconvGray(pixb, NULL, wc, hc);
+pixDestroy(&pixb);
+pixd = pixCreateRGBImage(pixrc, pixgc, pixbc);
+pixDestroy(&pixrc);
+pixDestroy(&pixgc);
+pixDestroy(&pixbc);
+}
+pixDestroy(&pixs);
+return pixd;
+}
+/*----------------------------------------------------------------------*
+*                     Grayscale block convolution                      *
+*----------------------------------------------------------------------*/
+/*!
+* \brief   pixBlockconvGray()
+*
+* \param[in]    pixs     8 bpp
+* \param[in]    pixacc   pix 32 bpp; can be null
+* \param[in]    wc, hc   half width/height of convolution kernel
+* \return  pix 8 bpp, or NULL on error
+*
+* <pre>
+* Notes:
+*      (1) If accum pix is null, make one and destroy it before
+*          returning; otherwise, just use the input accum pix.
+*      (2) The full width and height of the convolution kernel
+*          are (2 * wc + 1) and (2 * hc + 1).
+*      (3) Returns a copy if either wc or hc are 0
+*      (4) Require that w >= 2 * wc + 1 and h >= 2 * hc + 1,
+*          where (w,h) are the dimensions of pixs.  Attempt to
+*          reduce the kernel size if necessary.
+* </pre>
+*/
+PIX *
+pixBlockconvGray(PIX     *pixs,
+PIX     *pixacc,
+l_int32  wc,
+l_int32  hc)
+{
+l_int32    w, h, d, wpl, wpla;
+l_uint32  *datad, *dataa;
+PIX       *pixd, *pixt;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+pixGetDimensions(pixs, &w, &h, &d);
+if (d != 8)
+return (PIX *)ERROR_PTR("pixs not 8 bpp", __func__, NULL);
+if (wc <= 0 || hc <= 0)   /* no-op */
+return pixCopy(NULL, pixs);
+if (w < 2 * wc + 1 || h < 2 * hc + 1) {
+L_WARNING("kernel too large: wc = %d, hc = %d, w = %d, h = %d; "
+"reducing!\n", __func__, wc, hc, w, h);
+wc = L_MIN(wc, (w - 1) / 2);
+hc = L_MIN(hc, (h - 1) / 2);
+}
+if (wc == 0 || hc == 0)
+return pixCopy(NULL, pixs);
+if (pixacc) {
+if (pixGetDepth(pixacc) == 32) {
+pixt = pixClone(pixacc);
+} else {
+L_WARNING("pixacc not 32 bpp; making new one\n", __func__);
+if ((pixt = pixBlockconvAccum(pixs)) == NULL)
+return (PIX *)ERROR_PTR("pixt not made", __func__, NULL);
+}
+} else {
+if ((pixt = pixBlockconvAccum(pixs)) == NULL)
+return (PIX *)ERROR_PTR("pixt not made", __func__, NULL);
+}
+if ((pixd = pixCreateTemplate(pixs)) == NULL) {
+pixDestroy(&pixt);
+return (PIX *)ERROR_PTR("pixd not made", __func__, NULL);
+}
+pixSetPadBits(pixt, 0);
+wpl = pixGetWpl(pixd);
+wpla = pixGetWpl(pixt);
+datad = pixGetData(pixd);
+dataa = pixGetData(pixt);
+blockconvLow(datad, w, h, wpl, dataa, wpla, wc, hc);
+pixDestroy(&pixt);
+return pixd;
+}
+/*!
+* \brief   blockconvLow()
+*
+* \param[in]    data      data of input image, to be convolved
+* \param[in]    w, h, wpl
+* \param[in]    dataa     data of 32 bpp accumulator
+* \param[in]    wpla      accumulator
+* \param[in]    wc        convolution "half-width"
+* \param[in]    hc        convolution "half-height"
+* \return  void
+*
+* <pre>
+* Notes:
+*      (1) The full width and height of the convolution kernel
+*          are (2 * wc + 1) and (2 * hc + 1).
+*      (2) The lack of symmetry between the handling of the
+*          first (hc + 1) lines and the last (hc) lines,
+*          and similarly with the columns, is due to fact that
+*          for the pixel at (x,y), the accumulator values are
+*          taken at (x + wc, y + hc), (x - wc - 1, y + hc),
+*          (x + wc, y - hc - 1) and (x - wc - 1, y - hc - 1).
+*      (3) We compute sums, normalized as if there were no reduced
+*          area at the boundary.  This under-estimates the value
+*          of the boundary pixels, so we multiply them by another
+*          normalization factor that is greater than 1.
+*      (4) This second normalization is done first for the first
+*          hc + 1 lines; then for the last hc lines; and finally
+*          for the first wc + 1 and last wc columns in the intermediate
+*          lines.
+*      (5) The caller should verify that wc < w and hc < h.
+*          Failing either condition, illegal reads and writes can occur.
+*      (6) Implementation note: to get the same results in the interior
+*          between this function and pixConvolve(), it is necessary to
+*          add 0.5 for roundoff in the main loop that runs over all pixels.
+*          However, if we do that and have white (255) pixels near the
+*          image boundary, some overflow occurs for pixels very close
+*          to the boundary.  We can't fix this by subtracting from the
+*          normalized values for the boundary pixels, because this results
+*          in underflow if the boundary pixels are black (0).  Empirically,
+*          adding 0.25 (instead of 0.5) before truncating in the main
+*          loop will not cause overflow, but this gives some
+*          off-by-1-level errors in interior pixel values.  So we add
+*          0.5 for roundoff in the main loop, and for pixels within a
+*          half filter width of the boundary, use a L_MIN of the
+*          computed value and 255 to avoid overflow during normalization.
+* </pre>
+*/
+static void
+blockconvLow(l_uint32  *data,
+l_int32    w,
+l_int32    h,
+l_int32    wpl,
+l_uint32  *dataa,
+l_int32    wpla,
+l_int32    wc,
+l_int32    hc)
+{
+l_int32    i, j, imax, imin, jmax, jmin;
+l_int32    wn, hn, fwc, fhc, wmwc, hmhc;
+l_float32  norm, normh, normw;
+l_uint32   val;
+l_uint32  *linemina, *linemaxa, *line;
+wmwc = w - wc;
+hmhc = h - hc;
+if (wmwc <= 0 || hmhc <= 0) {
+L_ERROR("wc >= w || hc >= h\n", __func__);
+return;
+}
+fwc = 2 * wc + 1;
+fhc = 2 * hc + 1;
+norm = 1.0 / ((l_float32)(fwc) * fhc);
+/*------------------------------------------------------------*
+*  Compute, using b.c. only to set limits on the accum image *
+*------------------------------------------------------------*/
+for (i = 0; i < h; i++) {
+imin = L_MAX(i - 1 - hc, 0);
+imax = L_MIN(i + hc, h - 1);
+line = data + wpl * i;
+linemina = dataa + wpla * imin;
+linemaxa = dataa + wpla * imax;
+for (j = 0; j < w; j++) {
+jmin = L_MAX(j - 1 - wc, 0);
+jmax = L_MIN(j + wc, w - 1);
+val = linemaxa[jmax] - linemaxa[jmin]
++ linemina[jmin] - linemina[jmax];
+val = (l_uint8)(norm * val + 0.5);  /* see comment above */
+SET_DATA_BYTE(line, j, val);
+}
+}
+/*------------------------------------------------------------*
+*             Fix normalization for boundary pixels          *
+*------------------------------------------------------------*/
+for (i = 0; i <= hc; i++) {    /* first hc + 1 lines */
+hn = L_MAX(1, hc + i);
+normh = (l_float32)fhc / (l_float32)hn;   /* >= 1 */
+line = data + wpl * i;
+for (j = 0; j <= wc; j++) {
+wn = L_MAX(1, wc + j);
+normw = (l_float32)fwc / (l_float32)wn;   /* >= 1 */
+val = GET_DATA_BYTE(line, j);
+val = (l_uint8)L_MIN(val * normh * normw, 255);
+SET_DATA_BYTE(line, j, val);
+}
+for (j = wc + 1; j < wmwc; j++) {
+val = GET_DATA_BYTE(line, j);
+val = (l_uint8)L_MIN(val * normh, 255);
+SET_DATA_BYTE(line, j, val);
+}
+for (j = wmwc; j < w; j++) {
+wn = wc + w - j;
+normw = (l_float32)fwc / (l_float32)wn;   /* > 1 */
+val = GET_DATA_BYTE(line, j);
+val = (l_uint8)L_MIN(val * normh * normw, 255);
+SET_DATA_BYTE(line, j, val);
+}
+}
+for (i = hmhc; i < h; i++) {  /* last hc lines */
+hn = hc + h - i;
+normh = (l_float32)fhc / (l_float32)hn;   /* > 1 */
+line = data + wpl * i;
+for (j = 0; j <= wc; j++) {
+wn = wc + j;
+normw = (l_float32)fwc / (l_float32)wn;   /* > 1 */
+val = GET_DATA_BYTE(line, j);
+val = (l_uint8)L_MIN(val * normh * normw, 255);
+SET_DATA_BYTE(line, j, val);
+}
+for (j = wc + 1; j < wmwc; j++) {
+val = GET_DATA_BYTE(line, j);
+val = (l_uint8)L_MIN(val * normh, 255);
+SET_DATA_BYTE(line, j, val);
+}
+for (j = wmwc; j < w; j++) {
+wn = wc + w - j;
+normw = (l_float32)fwc / (l_float32)wn;   /* > 1 */
+val = GET_DATA_BYTE(line, j);
+val = (l_uint8)L_MIN(val * normh * normw, 255);
+SET_DATA_BYTE(line, j, val);
+}
+}
+for (i = hc + 1; i < hmhc; i++) {    /* intermediate lines */
+line = data + wpl * i;
+for (j = 0; j <= wc; j++) {   /* first wc + 1 columns */
+wn = wc + j;
+normw = (l_float32)fwc / (l_float32)wn;   /* > 1 */
+val = GET_DATA_BYTE(line, j);
+val = (l_uint8)L_MIN(val * normw, 255);
+SET_DATA_BYTE(line, j, val);
+}
+for (j = wmwc; j < w; j++) {   /* last wc columns */
+wn = wc + w - j;
+normw = (l_float32)fwc / (l_float32)wn;   /* > 1 */
+val = GET_DATA_BYTE(line, j);
+val = (l_uint8)L_MIN(val * normw, 255);
+SET_DATA_BYTE(line, j, val);
+}
+}
+}
+/*----------------------------------------------------------------------*
+*              Accumulator for 1, 8 and 32 bpp convolution             *
+*----------------------------------------------------------------------*/
+/*!
+* \brief   pixBlockconvAccum()
+*
+* \param[in]    pixs    1, 8 or 32 bpp
+* \return  accum pix 32 bpp, or NULL on error.
+*
+* <pre>
+* Notes:
+*      (1) The general recursion relation is
+*            a(i,j) = v(i,j) + a(i-1, j) + a(i, j-1) - a(i-1, j-1)
+*          For the first line, this reduces to the special case
+*            a(i,j) = v(i,j) + a(i, j-1)
+*          For the first column, the special case is
+*            a(i,j) = v(i,j) + a(i-1, j)
+* </pre>
+*/
+PIX *
+pixBlockconvAccum(PIX  *pixs)
+{
+l_int32    w, h, d, wpls, wpld;
+l_uint32  *datas, *datad;
+PIX       *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+pixGetDimensions(pixs, &w, &h, &d);
+if (d != 1 && d != 8 && d != 32)
+return (PIX *)ERROR_PTR("pixs not 1, 8 or 32 bpp", __func__, NULL);
+if ((pixd = pixCreate(w, h, 32)) == NULL)
+return (PIX *)ERROR_PTR("pixd not made", __func__, NULL);
+datas = pixGetData(pixs);
+datad = pixGetData(pixd);
+wpls = pixGetWpl(pixs);
+wpld = pixGetWpl(pixd);
+blockconvAccumLow(datad, w, h, wpld, datas, d, wpls);
+return pixd;
+}
+/*
+* \brief   blockconvAccumLow()
+*
+* \param[in]    datad         32 bpp dest
+* \param[in]    w, h, wpld    of 32 bpp dest
+* \param[in]    datas         1, 8 or 32 bpp src
+* \param[in]    d             bpp of src
+* \param[in]    wpls          of src
+* \return   void
+*
+* <pre>
+* Notes:
+*      (1) The general recursion relation is
+*             a(i,j) = v(i,j) + a(i-1, j) + a(i, j-1) - a(i-1, j-1)
+*          For the first line, this reduces to the special case
+*             a(0,j) = v(0,j) + a(0, j-1), j > 0
+*          For the first column, the special case is
+*             a(i,0) = v(i,0) + a(i-1, 0), i > 0
+* </pre>
+*/
+static void
+blockconvAccumLow(l_uint32  *datad,
+l_int32    w,
+l_int32    h,
+l_int32    wpld,
+l_uint32  *datas,
+l_int32    d,
+l_int32    wpls)
+{
+l_uint8    val;
+l_int32    i, j;
+l_uint32   val32;
+l_uint32  *lines, *lined, *linedp;
+lines = datas;
+lined = datad;
+if (d == 1) {
+/* Do the first line */
+for (j = 0; j < w; j++) {
+val = GET_DATA_BIT(lines, j);
+if (j == 0)
+lined[0] = val;
+else
+lined[j] = lined[j - 1] + val;
+}
+/* Do the other lines */
+for (i = 1; i < h; i++) {
+lines = datas + i * wpls;
+lined = datad + i * wpld;  /* curr dest line */
+linedp = lined - wpld;   /* prev dest line */
+for (j = 0; j < w; j++) {
+val = GET_DATA_BIT(lines, j);
+if (j == 0)
+lined[0] = val + linedp[0];
+else
+lined[j] = val + lined[j - 1] + linedp[j] - linedp[j - 1];
+}
+}
+} else if (d == 8) {
+/* Do the first line */
+for (j = 0; j < w; j++) {
+val = GET_DATA_BYTE(lines, j);
+if (j == 0)
+lined[0] = val;
+else
+lined[j] = lined[j - 1] + val;
+}
+/* Do the other lines */
+for (i = 1; i < h; i++) {
+lines = datas + i * wpls;
+lined = datad + i * wpld;  /* curr dest line */
+linedp = lined - wpld;   /* prev dest line */
+for (j = 0; j < w; j++) {
+val = GET_DATA_BYTE(lines, j);
+if (j == 0)
+lined[0] = val + linedp[0];
+else
+lined[j] = val + lined[j - 1] + linedp[j] - linedp[j - 1];
+}
+}
+} else if (d == 32) {
+/* Do the first line */
+for (j = 0; j < w; j++) {
+val32 = lines[j];
+if (j == 0)
+lined[0] = val32;
+else
+lined[j] = lined[j - 1] + val32;
+}
+/* Do the other lines */
+for (i = 1; i < h; i++) {
+lines = datas + i * wpls;
+lined = datad + i * wpld;  /* curr dest line */
+linedp = lined - wpld;   /* prev dest line */
+for (j = 0; j < w; j++) {
+val32 = lines[j];
+if (j == 0)
+lined[0] = val32 + linedp[0];
+else
+lined[j] = val32 + lined[j - 1] + linedp[j] - linedp[j - 1];
+}
+}
+} else {
+L_ERROR("depth not 1, 8 or 32 bpp\n", __func__);
+}
+}
+/*----------------------------------------------------------------------*
+*               Un-normalized grayscale block convolution              *
+*----------------------------------------------------------------------*/
+/*!
+* \brief   pixBlockconvGrayUnnormalized()
+*
+* \param[in]    pixs     8 bpp
+* \param[in]    wc, hc   half width/height of convolution kernel
+* \return  pix 32 bpp; containing the convolution without normalizing
+*                   for the window size, or NULL on error
+*
+* <pre>
+* Notes:
+*      (1) The full width and height of the convolution kernel
+*          are (2 * wc + 1) and (2 * hc + 1).
+*      (2) Require that w >= 2 * wc + 1 and h >= 2 * hc + 1,
+*          where (w,h) are the dimensions of pixs.  Attempt to
+*          reduce the kernel size if necessary.
+*      (3) Returns a copy if either wc or hc are 0.
+*      (3) Adds mirrored border to avoid treating the boundary pixels
+*          specially.  Note that we add wc + 1 pixels to the left
+*          and wc to the right.  The added width is 2 * wc + 1 pixels,
+*          and the particular choice simplifies the indexing in the loop.
+*          Likewise, add hc + 1 pixels to the top and hc to the bottom.
+*      (4) To get the normalized result, divide by the area of the
+*          convolution kernel: (2 * wc + 1) * (2 * hc + 1)
+*          Specifically, do this:
+*               pixc = pixBlockconvGrayUnnormalized(pixs, wc, hc);
+*               fract = 1. / ((2 * wc + 1) * (2 * hc + 1));
+*               pixMultConstantGray(pixc, fract);
+*               pixd = pixGetRGBComponent(pixc, L_ALPHA_CHANNEL);
+*      (5) Unlike pixBlockconvGray(), this always computes the accumulation
+*          pix because its size is tied to wc and hc.
+*      (6) Compare this implementation with pixBlockconvGray(), where
+*          most of the code in blockconvLow() is special casing for
+*          efficiently handling the boundary.  Here, the use of
+*          mirrored borders and destination indexing makes the
+*          implementation very simple.
+* </pre>
+*/
+PIX *
+pixBlockconvGrayUnnormalized(PIX     *pixs,
+l_int32  wc,
+l_int32  hc)
+{
+l_int32    i, j, w, h, d, wpla, wpld, jmax;
+l_uint32  *linemina, *linemaxa, *lined, *dataa, *datad;
+PIX       *pixsb, *pixacc, *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+pixGetDimensions(pixs, &w, &h, &d);
+if (d != 8)
+return (PIX *)ERROR_PTR("pixs not 8 bpp", __func__, NULL);
+if (wc <= 0 || hc <= 0)  /* no-op */
+return pixCopy(NULL, pixs);
+if (w < 2 * wc + 1 || h < 2 * hc + 1) {
+L_WARNING("kernel too large: wc = %d, hc = %d, w = %d, h = %d; "
+"reducing!\n", __func__, wc, hc, w, h);
+wc = L_MIN(wc, (w - 1) / 2);
+hc = L_MIN(hc, (h - 1) / 2);
+}
+if (wc == 0 || hc == 0)
+return pixCopy(NULL, pixs);
+if ((pixsb = pixAddMirroredBorder(pixs, wc + 1, wc, hc + 1, hc)) == NULL)
+return (PIX *)ERROR_PTR("pixsb not made", __func__, NULL);
+pixacc = pixBlockconvAccum(pixsb);
+pixDestroy(&pixsb);
+if (!pixacc)
+return (PIX *)ERROR_PTR("pixacc not made", __func__, NULL);
+if ((pixd = pixCreate(w, h, 32)) == NULL) {
+pixDestroy(&pixacc);
+return (PIX *)ERROR_PTR("pixd not made", __func__, NULL);
+}
+wpla = pixGetWpl(pixacc);
+wpld = pixGetWpl(pixd);
+datad = pixGetData(pixd);
+dataa = pixGetData(pixacc);
+for (i = 0; i < h; i++) {
+lined = datad + i * wpld;
+linemina = dataa + i * wpla;
+linemaxa = dataa + (i + 2 * hc + 1) * wpla;
+for (j = 0; j < w; j++) {
+jmax = j + 2 * wc + 1;
+lined[j] = linemaxa[jmax] - linemaxa[j] -
+linemina[jmax] + linemina[j];
+}
+}
+pixDestroy(&pixacc);
+return pixd;
+}
+/*----------------------------------------------------------------------*
+*               Tiled grayscale or color block convolution             *
+*----------------------------------------------------------------------*/
+/*!
+* \brief   pixBlockconvTiled()
+*
+* \param[in]    pix      8 or 32 bpp; or 2, 4 or 8 bpp with colormap
+* \param[in]    wc, hc   half width/height of convolution kernel
+* \param[in]    nx, ny   subdivision into tiles
+* \return  pixd, or NULL on error
+*
+* <pre>
+* Notes:
+*      (1) The full width and height of the convolution kernel
+*          are (2 * wc + 1) and (2 * hc + 1)
+*      (2) Returns a copy if either wc or hc are 0.
+*      (3) Require that w >= 2 * wc + 1 and h >= 2 * hc + 1,
+*          where (w,h) are the dimensions of pixs.  Attempt to
+*          reduce the kernel size if necessary.
+*      (4) For nx == ny == 1, this defaults to pixBlockconv(), which
+*          is typically about twice as fast, and gives nearly
+*          identical results as pixBlockconvGrayTile().
+*      (5) If the tiles are too small, nx and/or ny are reduced
+*          a minimum amount so that the tiles are expanded to the
+*          smallest workable size in the problematic direction(s).
+*      (6) Why a tiled version?  Three reasons:
+*          (a) Because the accumulator is a uint32, overflow can occur
+*              for an image with more than 16M pixels.
+*          (b) The accumulator array for 16M pixels is 64 MB; using
+*              tiles reduces the size of this array.
+*          (c) Each tile can be processed independently, in parallel,
+*              on a multicore processor.
+* </pre>
+*/
+PIX *
+pixBlockconvTiled(PIX     *pix,
+l_int32  wc,
+l_int32  hc,
+l_int32  nx,
+l_int32  ny)
+{
+l_int32     i, j, w, h, d, xrat, yrat;
+PIX        *pixs, *pixd, *pixc, *pixt;
+PIX        *pixr, *pixrc, *pixg, *pixgc, *pixb, *pixbc;
+PIXTILING  *pt;
+if (!pix)
+return (PIX *)ERROR_PTR("pix not defined", __func__, NULL);
+if (wc <= 0 || hc <= 0)   /* no-op */
+return pixCopy(NULL, pix);
+if (nx <= 1 && ny <= 1)
+return pixBlockconv(pix, wc, hc);
+pixGetDimensions(pix, &w, &h, &d);
+if (w < 2 * wc + 3 || h < 2 * hc + 3) {
+L_WARNING("kernel too large: wc = %d, hc = %d, w = %d, h = %d; "
+"reducing!\n", __func__, wc, hc, w, h);
+wc = L_MIN(wc, (w - 1) / 2);
+hc = L_MIN(hc, (h - 1) / 2);
+}
+if (wc == 0 || hc == 0)
+return pixCopy(NULL, pix);
+/* Test to see if the tiles are too small.  The required
+* condition is that the tile dimensions must be at least
+* (wc + 2) x (hc + 2). */
+xrat = w / nx;
+yrat = h / ny;
+if (xrat < wc + 2) {
+nx = w / (wc + 2);
+L_WARNING("tile width too small; nx reduced to %d\n", __func__, nx);
+}
+if (yrat < hc + 2) {
+ny = h / (hc + 2);
+L_WARNING("tile height too small; ny reduced to %d\n", __func__, ny);
+}
+/* Remove colormap if necessary */
+if ((d == 2 || d == 4 || d == 8) && pixGetColormap(pix)) {
+L_WARNING("pix has colormap; removing\n", __func__);
+pixs = pixRemoveColormap(pix, REMOVE_CMAP_BASED_ON_SRC);
+d = pixGetDepth(pixs);
+} else {
+pixs = pixClone(pix);
+}
+if (d != 8 && d != 32) {
+pixDestroy(&pixs);
+return (PIX *)ERROR_PTR("depth not 8 or 32 bpp", __func__, NULL);
+}
+/* Note that the overlaps in the width and height that
+* are added to the tile are (wc + 2) and (hc + 2).
+* These overlaps are removed by pixTilingPaintTile().
+* They are larger than the extent of the filter because
+* although the filter is symmetric with respect to its origin,
+* the implementation is asymmetric -- see the implementation in
+* pixBlockconvGrayTile(). */
+if ((pixd = pixCreateTemplate(pixs)) == NULL) {
+pixDestroy(&pixs);
+return (PIX *)ERROR_PTR("pixd not made", __func__, NULL);
+}
+pt = pixTilingCreate(pixs, nx, ny, 0, 0, wc + 2, hc + 2);
+for (i = 0; i < ny; i++) {
+for (j = 0; j < nx; j++) {
+pixt = pixTilingGetTile(pt, i, j);
+/* Convolve over the tile */
+if (d == 8) {
+pixc = pixBlockconvGrayTile(pixt, NULL, wc, hc);
+} else { /* d == 32 */
+pixr = pixGetRGBComponent(pixt, COLOR_RED);
+pixrc = pixBlockconvGrayTile(pixr, NULL, wc, hc);
+pixDestroy(&pixr);
+pixg = pixGetRGBComponent(pixt, COLOR_GREEN);
+pixgc = pixBlockconvGrayTile(pixg, NULL, wc, hc);
+pixDestroy(&pixg);
+pixb = pixGetRGBComponent(pixt, COLOR_BLUE);
+pixbc = pixBlockconvGrayTile(pixb, NULL, wc, hc);
+pixDestroy(&pixb);
+pixc = pixCreateRGBImage(pixrc, pixgc, pixbc);
+pixDestroy(&pixrc);
+pixDestroy(&pixgc);
+pixDestroy(&pixbc);
+}
+pixTilingPaintTile(pixd, i, j, pixc, pt);
+pixDestroy(&pixt);
+pixDestroy(&pixc);
+}
+}
+pixDestroy(&pixs);
+pixTilingDestroy(&pt);
+return pixd;
+}
+/*!
+* \brief   pixBlockconvGrayTile()
+*
+* \param[in]    pixs     8 bpp gray
+* \param[in]    pixacc   32 bpp accum pix
+* \param[in]    wc, hc   half width/height of convolution kernel
+* \return  pixd, or NULL on error
+*
+* <pre>
+* Notes:
+*      (1) The full width and height of the convolution kernel
+*          are (2 * wc + 1) and (2 * hc + 1)
+*      (2) Assumes that the input pixs is padded with (wc + 1) pixels on
+*          left and right, and with (hc + 1) pixels on top and bottom.
+*          The returned pix has these stripped off; they are only used
+*          for computation.
+*      (3) Returns a copy if either wc or hc are 0.
+*      (4) Require that w > 2 * wc + 3 and h > 2 * hc + 3,
+*          where (w,h) are the dimensions of pixs.  Attempt to
+*          reduce the kernel size if necessary.
+* </pre>
+*/
+PIX *
+pixBlockconvGrayTile(PIX     *pixs,
+PIX     *pixacc,
+l_int32  wc,
+l_int32  hc)
+{
+l_int32    w, h, d, wd, hd, i, j, imin, imax, jmin, jmax, wplt, wpld;
+l_float32  norm;
+l_uint32   val;
+l_uint32  *datat, *datad, *lined, *linemint, *linemaxt;
+PIX       *pixt, *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pix not defined", __func__, NULL);
+pixGetDimensions(pixs, &w, &h, &d);
+if (d != 8)
+return (PIX *)ERROR_PTR("pixs not 8 bpp", __func__, NULL);
+if (wc <= 0 || hc <= 0)  /* no-op */
+return pixCopy(NULL, pixs);
+if (w < 2 * wc + 3 || h < 2 * hc + 3) {
+L_WARNING("kernel too large: wc = %d, hc = %d, w = %d, h = %d; "
+"reducing!\n", __func__, wc, hc, w, h);
+wc = L_MIN(wc, (w - 1) / 2);
+hc = L_MIN(hc, (h - 1) / 2);
+}
+if (wc == 0 || hc == 0)
+return pixCopy(NULL, pixs);
+wd = w - 2 * wc;
+hd = h - 2 * hc;
+if (pixacc) {
+if (pixGetDepth(pixacc) == 32) {
+pixt = pixClone(pixacc);
+} else {
+L_WARNING("pixacc not 32 bpp; making new one\n", __func__);
+if ((pixt = pixBlockconvAccum(pixs)) == NULL)
+return (PIX *)ERROR_PTR("pixt not made", __func__, NULL);
+}
+} else {
+if ((pixt = pixBlockconvAccum(pixs)) == NULL)
+return (PIX *)ERROR_PTR("pixt not made", __func__, NULL);
+}
+if ((pixd = pixCreateTemplate(pixs)) == NULL) {
+pixDestroy(&pixt);
+return (PIX *)ERROR_PTR("pixd not made", __func__, NULL);
+}
+datat = pixGetData(pixt);
+wplt = pixGetWpl(pixt);
+datad = pixGetData(pixd);
+wpld = pixGetWpl(pixd);
+norm = 1. / (l_float32)((2 * wc + 1) * (2 * hc + 1));
+/* Do the convolution over the subregion of size (wd - 2, hd - 2),
+* which exactly corresponds to the size of the subregion that
+* will be extracted by pixTilingPaintTile().  Note that the
+* region in which points are computed is not symmetric about
+* the center of the images; instead the computation in
+* the accumulator image is shifted up and to the left by 1,
+* relative to the center, because the 4 accumulator sampling
+* points are taken at the LL corner of the filter and at 3 other
+* points that are shifted -wc and -hc to the left and above.  */
+for (i = hc; i < hc + hd - 2; i++) {
+imin = L_MAX(i - hc - 1, 0);
+imax = L_MIN(i + hc, h - 1);
+lined = datad + i * wpld;
+linemint = datat + imin * wplt;
+linemaxt = datat + imax * wplt;
+for (j = wc; j < wc + wd - 2; j++) {
+jmin = L_MAX(j - wc - 1, 0);
+jmax = L_MIN(j + wc, w - 1);
+val = linemaxt[jmax] - linemaxt[jmin]
++ linemint[jmin] - linemint[jmax];
+val = (l_uint8)(norm * val + 0.5);
+SET_DATA_BYTE(lined, j, val);
+}
+}
+pixDestroy(&pixt);
+return pixd;
+}
+/*----------------------------------------------------------------------*
+*     Convolution for mean, mean square, variance and rms deviation    *
+*----------------------------------------------------------------------*/
+/*!
+* \brief   pixWindowedStats()
+*
+* \param[in]    pixs        8 bpp grayscale
+* \param[in]    wc, hc      half width/height of convolution kernel
+* \param[in]    hasborder   use 1 if it already has (wc + 1 border pixels
+*                           on left and right, and hc + 1 on top and bottom;
+*                           use 0 to add kernel-dependent border)
+* \param[out]   ppixm       [optional] 8 bpp mean value in window
+* \param[out]   ppixms      [optional] 32 bpp mean square value in window
+* \param[out]   pfpixv      [optional] float variance in window
+* \param[out]   pfpixrv     [optional] float rms deviation from the mean
+* \return  0 if OK, 1 on error
+*
+* <pre>
+* Notes:
+*      (1) This is a high-level convenience function for calculating
+*          any or all of these derived images.
+*      (2) If %hasborder = 0, a border is added and the result is
+*          computed over all pixels in pixs.  Otherwise, no border is
+*          added and the border pixels are removed from the output images.
+*      (3) These statistical measures over the pixels in the
+*          rectangular window are:
+*            ~ average value: <p>  (pixm)
+*            ~ average squared value: <p*p> (pixms)
+*            ~ variance: <(p - <p>)*(p - <p>)> = <p*p> - <p>*<p>  (pixv)
+*            ~ square-root of variance: (pixrv)
+*          where the brackets < .. > indicate that the average value is
+*          to be taken over the window.
+*      (4) Note that the variance is just the mean square difference from
+*          the mean value; and the square root of the variance is the
+*          root mean square difference from the mean, sometimes also
+*          called the 'standard deviation'.
+*      (5) The added border, along with the use of an accumulator array,
+*          allows computation without special treatment of pixels near
+*          the image boundary, and runs in a time that is independent
+*          of the size of the convolution kernel.
+* </pre>
+*/
+l_ok
+pixWindowedStats(PIX     *pixs,
+l_int32  wc,
+l_int32  hc,
+l_int32  hasborder,
+PIX    **ppixm,
+PIX    **ppixms,
+FPIX   **pfpixv,
+FPIX   **pfpixrv)
+{
+PIX  *pixb, *pixm, *pixms;
+if (!ppixm && !ppixms && !pfpixv && !pfpixrv)
+return ERROR_INT("no output requested", __func__, 1);
+if (ppixm) *ppixm = NULL;
+if (ppixms) *ppixms = NULL;
+if (pfpixv) *pfpixv = NULL;
+if (pfpixrv) *pfpixrv = NULL;
+if (!pixs || pixGetDepth(pixs) != 8)
+return ERROR_INT("pixs not defined or not 8 bpp", __func__, 1);
+if (wc < 2 || hc < 2)
+return ERROR_INT("wc and hc not >= 2", __func__, 1);
+/* Add border if requested */
+if (!hasborder)
+pixb = pixAddBorderGeneral(pixs, wc + 1, wc + 1, hc + 1, hc + 1, 0);
+else
+pixb = pixClone(pixs);
+if (!pfpixv && !pfpixrv) {
+if (ppixm) *ppixm = pixWindowedMean(pixb, wc, hc, 1, 1);
+if (ppixms) *ppixms = pixWindowedMeanSquare(pixb, wc, hc, 1);
+pixDestroy(&pixb);
+return 0;
+}
+pixm = pixWindowedMean(pixb, wc, hc, 1, 1);
+pixms = pixWindowedMeanSquare(pixb, wc, hc, 1);
+pixWindowedVariance(pixm, pixms, pfpixv, pfpixrv);
+if (ppixm)
+*ppixm = pixm;
+else
+pixDestroy(&pixm);
+if (ppixms)
+*ppixms = pixms;
+else
+pixDestroy(&pixms);
+pixDestroy(&pixb);
+return 0;
+}
+/*!
+* \brief   pixWindowedMean()
+*
+* \param[in]    pixs        8 or 32 bpp grayscale
+* \param[in]    wc, hc      half width/height of convolution kernel
+* \param[in]    hasborder   use 1 if it already has (wc + 1 border pixels
+*                           on left and right, and hc + 1 on top and bottom;
+*                           use 0 to add kernel-dependent border)
+* \param[in]    normflag    1 for normalization to get average in window;
+*                           0 for the sum in the window (un-normalized)
+* \return  pixd 8 or 32 bpp, average over kernel window
+*
+* <pre>
+* Notes:
+*      (1) The input and output depths are the same.
+*      (2) A set of border pixels of width (wc + 1) on left and right,
+*          and of height (hc + 1) on top and bottom, must be on the
+*          pix before the accumulator is found.  The output pixd
+*          (after convolution) has this border removed.
+*          If %hasborder = 0, the required border is added.
+*      (3) Typically, %normflag == 1.  However, if you want the sum
+*          within the window, rather than a normalized convolution,
+*          use %normflag == 0.
+*      (4) This builds a block accumulator pix, uses it here, and
+*          destroys it.
+*      (5) The added border, along with the use of an accumulator array,
+*          allows computation without special treatment of pixels near
+*          the image boundary, and runs in a time that is independent
+*          of the size of the convolution kernel.
+* </pre>
+*/
+PIX *
+pixWindowedMean(PIX     *pixs,
+l_int32  wc,
+l_int32  hc,
+l_int32  hasborder,
+l_int32  normflag)
+{
+l_int32    i, j, w, h, d, wd, hd, wplc, wpld, wincr, hincr;
+l_uint32   val;
+l_uint32  *datac, *datad, *linec1, *linec2, *lined;
+l_float32  norm;
+PIX       *pixb, *pixc, *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+d = pixGetDepth(pixs);
+if (d != 8 && d != 32)
+return (PIX *)ERROR_PTR("pixs not 8 or 32 bpp", __func__, NULL);
+if (wc < 2 || hc < 2)
+return (PIX *)ERROR_PTR("wc and hc not >= 2", __func__, NULL);
+pixb = pixc = pixd = NULL;
+/* Add border if requested */
+if (!hasborder)
+pixb = pixAddBorderGeneral(pixs, wc + 1, wc + 1, hc + 1, hc + 1, 0);
+else
+pixb = pixClone(pixs);
+/* Make the accumulator pix from pixb */
+if ((pixc = pixBlockconvAccum(pixb)) == NULL) {
+L_ERROR("pixc not made\n", __func__);
+goto cleanup;
+}
+wplc = pixGetWpl(pixc);
+datac = pixGetData(pixc);
+/* The output has wc + 1 border pixels stripped from each side
+* of pixb, and hc + 1 border pixels stripped from top and bottom. */
+pixGetDimensions(pixb, &w, &h, NULL);
+wd = w - 2 * (wc + 1);
+hd = h - 2 * (hc + 1);
+if (wd < 2 || hd < 2) {
+L_ERROR("w or h is too small for the kernel\n", __func__);
+goto cleanup;
+}
+if ((pixd = pixCreate(wd, hd, d)) == NULL) {
+L_ERROR("pixd not made\n", __func__);
+goto cleanup;
+}
+wpld = pixGetWpl(pixd);
+datad = pixGetData(pixd);
+wincr = 2 * wc + 1;
+hincr = 2 * hc + 1;
+norm = 1.0;  /* use this for sum-in-window */
+if (normflag)
+norm = 1.0 / ((l_float32)(wincr) * hincr);
+for (i = 0; i < hd; i++) {
+linec1 = datac + i * wplc;
+linec2 = datac + (i + hincr) * wplc;
+lined = datad + i * wpld;
+for (j = 0; j < wd; j++) {
+val = linec2[j + wincr] - linec2[j] - linec1[j + wincr] + linec1[j];
+if (d == 8) {
+val = (l_uint8)(norm * val);
+SET_DATA_BYTE(lined, j, val);
+} else {  /* d == 32 */
+val = (l_uint32)(norm * val);
+lined[j] = val;
+}
+}
+}
+cleanup:
+pixDestroy(&pixb);
+pixDestroy(&pixc);
+return pixd;
+}
+/*!
+* \brief   pixWindowedMeanSquare()
+*
+* \param[in]    pixs        8 bpp grayscale
+* \param[in]    wc, hc      half width/height of convolution kernel
+* \param[in]    hasborder   use 1 if it already has (wc + 1 border pixels
+*                           on left and right, and hc + 1 on top and bottom;
+*                           use 0 to add kernel-dependent border)
+* \return  pixd    32 bpp, average over rectangular window of
+*                  width = 2 * wc + 1 and height = 2 * hc + 1
+*
+* <pre>
+* Notes:
+*      (1) A set of border pixels of width (wc + 1) on left and right,
+*          and of height (hc + 1) on top and bottom, must be on the
+*          pix before the accumulator is found.  The output pixd
+*          (after convolution) has this border removed.
+*          If %hasborder = 0, the required border is added.
+*      (2) The advantage is that we are unaffected by the boundary, and
+*          it is not necessary to treat pixels within %wc and %hc of the
+*          border differently.  This is because processing for pixd
+*          only takes place for pixels in pixs for which the
+*          kernel is entirely contained in pixs.
+*      (3) Why do we have an added border of width (%wc + 1) and
+*          height (%hc + 1), when we only need %wc and %hc pixels
+*          to satisfy this condition?  Answer: the accumulators
+*          are asymmetric, requiring an extra row and column of
+*          pixels at top and left to work accurately.
+*      (4) The added border, along with the use of an accumulator array,
+*          allows computation without special treatment of pixels near
+*          the image boundary, and runs in a time that is independent
+*          of the size of the convolution kernel.
+* </pre>
+*/
+PIX *
+pixWindowedMeanSquare(PIX     *pixs,
+l_int32  wc,
+l_int32  hc,
+l_int32  hasborder)
+{
+l_int32     i, j, w, h, wd, hd, wpl, wpld, wincr, hincr;
+l_uint32    ival;
+l_uint32   *datad, *lined;
+l_float64   norm;
+l_float64   val;
+l_float64  *data, *line1, *line2;
+DPIX       *dpix;
+PIX        *pixb, *pixd;
+if (!pixs || (pixGetDepth(pixs) != 8))
+return (PIX *)ERROR_PTR("pixs undefined or not 8 bpp", __func__, NULL);
+if (wc < 2 || hc < 2)
+return (PIX *)ERROR_PTR("wc and hc not >= 2", __func__, NULL);
+pixd = NULL;
+/* Add border if requested */
+if (!hasborder)
+pixb = pixAddBorderGeneral(pixs, wc + 1, wc + 1, hc + 1, hc + 1, 0);
+else
+pixb = pixClone(pixs);
+if ((dpix = pixMeanSquareAccum(pixb)) == NULL) {
+L_ERROR("dpix not made\n", __func__);
+goto cleanup;
+}
+wpl = dpixGetWpl(dpix);
+data = dpixGetData(dpix);
+/* The output has wc + 1 border pixels stripped from each side
+* of pixb, and hc + 1 border pixels stripped from top and bottom. */
+pixGetDimensions(pixb, &w, &h, NULL);
+wd = w - 2 * (wc + 1);
+hd = h - 2 * (hc + 1);
+if (wd < 2 || hd < 2) {
+L_ERROR("w or h too small for kernel\n", __func__);
+goto cleanup;
+}
+if ((pixd = pixCreate(wd, hd, 32)) == NULL) {
+L_ERROR("pixd not made\n", __func__);
+goto cleanup;
+}
+wpld = pixGetWpl(pixd);
+datad = pixGetData(pixd);
+wincr = 2 * wc + 1;
+hincr = 2 * hc + 1;
+norm = 1.0 / ((l_float32)(wincr) * hincr);
+for (i = 0; i < hd; i++) {
+line1 = data + i * wpl;
+line2 = data + (i + hincr) * wpl;
+lined = datad + i * wpld;
+for (j = 0; j < wd; j++) {
+val = line2[j + wincr] - line2[j] - line1[j + wincr] + line1[j];
+ival = (l_uint32)(norm * val + 0.5);  /* to round up */
+lined[j] = ival;
+}
+}
+cleanup:
+dpixDestroy(&dpix);
+pixDestroy(&pixb);
+return pixd;
+}
+/*!
+* \brief   pixWindowedVariance()
+*
+* \param[in]    pixm      mean over window; 8 or 32 bpp grayscale
+* \param[in]    pixms     mean square over window; 32 bpp
+* \param[out]   pfpixv    [optional] float variance -- the ms deviation
+*                         from the mean
+* \param[out]   pfpixrv   [optional] float rms deviation from the mean
+* \return  0 if OK, 1 on error
+*
+* <pre>
+* Notes:
+*      (1) The mean and mean square values are precomputed, using
+*          pixWindowedMean() and pixWindowedMeanSquare().
+*      (2) Either or both of the variance and square-root of variance
+*          are returned as an fpix, where the variance is the
+*          average over the window of the mean square difference of
+*          the pixel value from the mean:
+*                <(p - <p>)*(p - <p>)> = <p*p> - <p>*<p>
+*      (3) To visualize the results:
+*            ~ for both, use fpixDisplayMaxDynamicRange().
+*            ~ for rms deviation, simply convert the output fpix to pix,
+* </pre>
+*/
+l_ok
+pixWindowedVariance(PIX    *pixm,
+PIX    *pixms,
+FPIX  **pfpixv,
+FPIX  **pfpixrv)
+{
+l_int32     i, j, w, h, ws, hs, ds, wplm, wplms, wplv, wplrv, valm, valms;
+l_float32   var;
+l_uint32   *linem, *linems, *datam, *datams;
+l_float32  *linev = NULL, *linerv = NULL, *datav = NULL, *datarv = NULL;
+FPIX       *fpixv, *fpixrv;  /* variance and square root of variance */
+if (!pfpixv && !pfpixrv)
+return ERROR_INT("no output requested", __func__, 1);
+if (pfpixv) *pfpixv = NULL;
+if (pfpixrv) *pfpixrv = NULL;
+if (!pixm || pixGetDepth(pixm) != 8)
+return ERROR_INT("pixm undefined or not 8 bpp", __func__, 1);
+if (!pixms || pixGetDepth(pixms) != 32)
+return ERROR_INT("pixms undefined or not 32 bpp", __func__, 1);
+pixGetDimensions(pixm, &w, &h, NULL);
+pixGetDimensions(pixms, &ws, &hs, &ds);
+if (w != ws || h != hs)
+return ERROR_INT("pixm and pixms sizes differ", __func__, 1);
+if (pfpixv) {
+fpixv = fpixCreate(w, h);
+*pfpixv = fpixv;
+wplv = fpixGetWpl(fpixv);
+datav = fpixGetData(fpixv);
+}
+if (pfpixrv) {
+fpixrv = fpixCreate(w, h);
+*pfpixrv = fpixrv;
+wplrv = fpixGetWpl(fpixrv);
+datarv = fpixGetData(fpixrv);
+}
+wplm = pixGetWpl(pixm);
+wplms = pixGetWpl(pixms);
+datam = pixGetData(pixm);
+datams = pixGetData(pixms);
+for (i = 0; i < h; i++) {
+linem = datam + i * wplm;
+linems = datams + i * wplms;
+if (pfpixv)
+linev = datav + i * wplv;
+if (pfpixrv)
+linerv = datarv + i * wplrv;
+for (j = 0; j < w; j++) {
+valm = GET_DATA_BYTE(linem, j);
+if (ds == 8)
+valms = GET_DATA_BYTE(linems, j);
+else  /* ds == 32 */
+valms = (l_int32)linems[j];
+var = (l_float32)valms - (l_float32)valm * valm;
+if (pfpixv)
+linev[j] = var;
+if (pfpixrv)
+linerv[j] = (l_float32)sqrt(var);
+}
+}
+return 0;
+}
+/*!
+* \brief   pixMeanSquareAccum()
+*
+* \param[in]    pixs    8 bpp grayscale
+* \return  dpix   64 bit array, or NULL on error
+*
+* <pre>
+* Notes:
+*      (1) Similar to pixBlockconvAccum(), this computes the
+*          sum of the squares of the pixel values in such a way
+*          that the value at (i,j) is the sum of all squares in
+*          the rectangle from the origin to (i,j).
+*      (2) The general recursion relation (v are squared pixel values) is
+*            a(i,j) = v(i,j) + a(i-1, j) + a(i, j-1) - a(i-1, j-1)
+*          For the first line, this reduces to the special case
+*            a(i,j) = v(i,j) + a(i, j-1)
+*          For the first column, the special case is
+*            a(i,j) = v(i,j) + a(i-1, j)
+* </pre>
+*/
+DPIX *
+pixMeanSquareAccum(PIX  *pixs)
+{
+l_int32     i, j, w, h, wpl, wpls, val;
+l_uint32   *datas, *lines;
+l_float64  *data, *line, *linep;
+DPIX       *dpix;
+if (!pixs || (pixGetDepth(pixs) != 8))
+return (DPIX *)ERROR_PTR("pixs undefined or not 8 bpp", __func__, NULL);
+pixGetDimensions(pixs, &w, &h, NULL);
+if ((dpix = dpixCreate(w, h)) ==  NULL)
+return (DPIX *)ERROR_PTR("dpix not made", __func__, NULL);
+datas = pixGetData(pixs);
+wpls = pixGetWpl(pixs);
+data = dpixGetData(dpix);
+wpl = dpixGetWpl(dpix);
+lines = datas;
+line = data;
+for (j = 0; j < w; j++) {   /* first line */
+val = GET_DATA_BYTE(lines, j);
+if (j == 0)
+line[0] = (l_float64)(val) * val;
+else
+line[j] = line[j - 1] + (l_float64)(val) * val;
+}
+/* Do the other lines */
+for (i = 1; i < h; i++) {
+lines = datas + i * wpls;
+line = data + i * wpl;  /* current dest line */
+linep = line - wpl;;  /* prev dest line */
+for (j = 0; j < w; j++) {
+val = GET_DATA_BYTE(lines, j);
+if (j == 0)
+line[0] = linep[0] + (l_float64)(val) * val;
+else
+line[j] = line[j - 1] + linep[j] - linep[j - 1]
++ (l_float64)(val) * val;
+}
+}
+return dpix;
+}
+/*----------------------------------------------------------------------*
+*                        Binary block sum/rank                         *
+*----------------------------------------------------------------------*/
+/*!
+* \brief   pixBlockrank()
+*
+* \param[in]    pixs     1 bpp
+* \param[in]    pixacc   pix [optional] 32 bpp
+* \param[in]    wc, hc   half width/height of block sum/rank kernel
+* \param[in]    rank     between 0.0 and 1.0; 0.5 is median filter
+* \return  pixd 1 bpp
+*
+* <pre>
+* Notes:
+*      (1) The full width and height of the convolution kernel
+*          are (2 * wc + 1) and (2 * hc + 1)
+*      (2) This returns a pixd where each pixel is a 1 if the
+*          neighborhood (2 * wc + 1) x (2 * hc + 1)) pixels
+*          contains the rank fraction of 1 pixels.  Otherwise,
+*          the returned pixel is 0.  Note that the special case
+*          of rank = 0.0 is always satisfied, so the returned
+*          pixd has all pixels with value 1.
+*      (3) If accum pix is null, make one, use it, and destroy it
+*          before returning; otherwise, just use the input accum pix
+*      (4) If both wc and hc are 0, returns a copy unless rank == 0.0,
+*          in which case this returns an all-ones image.
+*      (5) Require that w >= 2 * wc + 1 and h >= 2 * hc + 1,
+*          where (w,h) are the dimensions of pixs.  Attempt to
+*          reduce the kernel size if necessary.
+* </pre>
+*/
+PIX *
+pixBlockrank(PIX       *pixs,
+PIX       *pixacc,
+l_int32    wc,
+l_int32    hc,
+l_float32  rank)
+{
+l_int32  w, h, d, thresh;
+PIX     *pixt, *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+pixGetDimensions(pixs, &w, &h, &d);
+if (d != 1)
+return (PIX *)ERROR_PTR("pixs not 1 bpp", __func__, NULL);
+if (rank < 0.0 || rank > 1.0)
+return (PIX *)ERROR_PTR("rank must be in [0.0, 1.0]", __func__, NULL);
+if (rank == 0.0) {
+pixd = pixCreateTemplate(pixs);
+pixSetAll(pixd);
+return pixd;
+}
+if (wc <= 0 || hc <= 0)
+return pixCopy(NULL, pixs);
+if (w < 2 * wc + 1 || h < 2 * hc + 1) {
+L_WARNING("kernel too large: wc = %d, hc = %d, w = %d, h = %d; "
+"reducing!\n", __func__, wc, hc, w, h);
+wc = L_MIN(wc, (w - 1) / 2);
+hc = L_MIN(hc, (h - 1) / 2);
+}
+if (wc == 0 || hc == 0)
+return pixCopy(NULL, pixs);
+if ((pixt = pixBlocksum(pixs, pixacc, wc, hc)) == NULL)
+return (PIX *)ERROR_PTR("pixt not made", __func__, NULL);
+/* 1 bpp block rank filter output.
+* Must invert because threshold gives 1 for values < thresh,
+* but we need a 1 if the value is >= thresh. */
+thresh = (l_int32)(255. * rank);
+pixd = pixThresholdToBinary(pixt, thresh);
+pixInvert(pixd, pixd);
+pixDestroy(&pixt);
+return pixd;
+}
+/*!
+* \brief   pixBlocksum()
+*
+* \param[in]    pixs     1 bpp
+* \param[in]    pixacc   pix [optional] 32 bpp
+* \param[in]    wc, hc   half width/height of block sum/rank kernel
+* \return  pixd 8 bpp
+*
+* <pre>
+* Notes:
+*      (1) If accum pix is null, make one and destroy it before
+*          returning; otherwise, just use the input accum pix
+*      (2) The full width and height of the convolution kernel
+*          are (2 * wc + 1) and (2 * hc + 1)
+*      (3) Use of wc = hc = 1, followed by pixInvert() on the
+*          8 bpp result, gives a nice anti-aliased, and somewhat
+*          darkened, result on text.
+*      (4) Require that w >= 2 * wc + 1 and h >= 2 * hc + 1,
+*          where (w,h) are the dimensions of pixs.  Attempt to
+*          reduce the kernel size if necessary.
+*      (5) Returns in each dest pixel the sum of all src pixels
+*          that are within a block of size of the kernel, centered
+*          on the dest pixel.  This sum is the number of src ON
+*          pixels in the block at each location, normalized to 255
+*          for a block containing all ON pixels.  For pixels near
+*          the boundary, where the block is not entirely contained
+*          within the image, we then multiply by a second normalization
+*          factor that is greater than one, so that all results
+*          are normalized by the number of participating pixels
+*          within the block.
+* </pre>
+*/
+PIX *
+pixBlocksum(PIX     *pixs,
+PIX     *pixacc,
+l_int32  wc,
+l_int32  hc)
+{
+l_int32    w, h, d, wplt, wpld;
+l_uint32  *datat, *datad;
+PIX       *pixt, *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+pixGetDimensions(pixs, &w, &h, &d);
+if (d != 1)
+return (PIX *)ERROR_PTR("pixs not 1 bpp", __func__, NULL);
+if (wc <= 0 || hc <= 0)
+return pixCopy(NULL, pixs);
+if (w < 2 * wc + 1 || h < 2 * hc + 1) {
+L_WARNING("kernel too large: wc = %d, hc = %d, w = %d, h = %d; "
+"reducing!\n", __func__, wc, hc, w, h);
+wc = L_MIN(wc, (w - 1) / 2);
+hc = L_MIN(hc, (h - 1) / 2);
+}
+if (wc == 0 || hc == 0)
+return pixCopy(NULL, pixs);
+if (pixacc) {
+if (pixGetDepth(pixacc) != 32)
+return (PIX *)ERROR_PTR("pixacc not 32 bpp", __func__, NULL);
+pixt = pixClone(pixacc);
+} else {
+if ((pixt = pixBlockconvAccum(pixs)) == NULL)
+return (PIX *)ERROR_PTR("pixt not made", __func__, NULL);
+}
+/* 8 bpp block sum output */
+if ((pixd = pixCreate(w, h, 8)) == NULL) {
+pixDestroy(&pixt);
+return (PIX *)ERROR_PTR("pixd not made", __func__, NULL);
+}
+pixCopyResolution(pixd, pixs);
+wpld = pixGetWpl(pixd);
+wplt = pixGetWpl(pixt);
+datad = pixGetData(pixd);
+datat = pixGetData(pixt);
+blocksumLow(datad, w, h, wpld, datat, wplt, wc, hc);
+pixDestroy(&pixt);
+return pixd;
+}
+/*!
+* \brief   blocksumLow()
+*
+* \param[in]    datad        of 8 bpp dest
+* \param[in]    w, h, wpl    of 8 bpp dest
+* \param[in]    dataa        of 32 bpp accum
+* \param[in]    wpla         of 32 bpp accum
+* \param[in]    wc, hc       convolution "half-width" and "half-height"
+* \return  void
+*
+* <pre>
+* Notes:
+*      (1) The full width and height of the convolution kernel
+*          are (2 * wc + 1) and (2 * hc + 1).
+*      (2) The lack of symmetry between the handling of the
+*          first (hc + 1) lines and the last (hc) lines,
+*          and similarly with the columns, is due to fact that
+*          for the pixel at (x,y), the accumulator values are
+*          taken at (x + wc, y + hc), (x - wc - 1, y + hc),
+*          (x + wc, y - hc - 1) and (x - wc - 1, y - hc - 1).
+*      (3) Compute sums of ON pixels within the block filter size,
+*          normalized between 0 and 255, as if there were no reduced
+*          area at the boundary.  This under-estimates the value
+*          of the boundary pixels, so we multiply them by another
+*          normalization factor that is greater than 1.
+*      (4) This second normalization is done first for the first
+*          hc + 1 lines; then for the last hc lines; and finally
+*          for the first wc + 1 and last wc columns in the intermediate
+*          lines.
+*      (5) Required constraints are: wc < w and hc < h.
+* </pre>
+*/
+static void
+blocksumLow(l_uint32  *datad,
+l_int32    w,
+l_int32    h,
+l_int32    wpl,
+l_uint32  *dataa,
+l_int32    wpla,
+l_int32    wc,
+l_int32    hc)
+{
+l_int32    i, j, imax, imin, jmax, jmin;
+l_int32    wn, hn, fwc, fhc, wmwc, hmhc;
+l_float32  norm, normh, normw;
+l_uint32   val;
+l_uint32  *linemina, *linemaxa, *lined;
+wmwc = w - wc;
+hmhc = h - hc;
+if (wmwc <= 0 || hmhc <= 0) {
+L_ERROR("wc >= w || hc >=h\n", __func__);
+return;
+}
+fwc = 2 * wc + 1;
+fhc = 2 * hc + 1;
+norm = 255. / ((l_float32)(fwc) * fhc);
+/*------------------------------------------------------------*
+*  Compute, using b.c. only to set limits on the accum image *
+*------------------------------------------------------------*/
+for (i = 0; i < h; i++) {
+imin = L_MAX(i - 1 - hc, 0);
+imax = L_MIN(i + hc, h - 1);
+lined = datad + wpl * i;
+linemina = dataa + wpla * imin;
+linemaxa = dataa + wpla * imax;
+for (j = 0; j < w; j++) {
+jmin = L_MAX(j - 1 - wc, 0);
+jmax = L_MIN(j + wc, w - 1);
+val = linemaxa[jmax] - linemaxa[jmin]
+- linemina[jmax] + linemina[jmin];
+val = (l_uint8)(norm * val);
+SET_DATA_BYTE(lined, j, val);
+}
+}
+/*------------------------------------------------------------*
+*             Fix normalization for boundary pixels          *
+*------------------------------------------------------------*/
+for (i = 0; i <= hc; i++) {    /* first hc + 1 lines */
+hn = hc + i;
+normh = (l_float32)fhc / (l_float32)hn;   /* > 1 */
+lined = datad + wpl * i;
+for (j = 0; j <= wc; j++) {
+wn = wc + j;
+normw = (l_float32)fwc / (l_float32)wn;   /* > 1 */
+val = GET_DATA_BYTE(lined, j);
+val = (l_uint8)(val * normh * normw);
+SET_DATA_BYTE(lined, j, val);
+}
+for (j = wc + 1; j < wmwc; j++) {
+val = GET_DATA_BYTE(lined, j);
+val = (l_uint8)(val * normh);
+SET_DATA_BYTE(lined, j, val);
+}
+for (j = wmwc; j < w; j++) {
+wn = wc + w - j;
+normw = (l_float32)fwc / (l_float32)wn;   /* > 1 */
+val = GET_DATA_BYTE(lined, j);
+val = (l_uint8)(val * normh * normw);
+SET_DATA_BYTE(lined, j, val);
+}
+}
+for (i = hmhc; i < h; i++) {  /* last hc lines */
+hn = hc + h - i;
+normh = (l_float32)fhc / (l_float32)hn;   /* > 1 */
+lined = datad + wpl * i;
+for (j = 0; j <= wc; j++) {
+wn = wc + j;
+normw = (l_float32)fwc / (l_float32)wn;   /* > 1 */
+val = GET_DATA_BYTE(lined, j);
+val = (l_uint8)(val * normh * normw);
+SET_DATA_BYTE(lined, j, val);
+}
+for (j = wc + 1; j < wmwc; j++) {
+val = GET_DATA_BYTE(lined, j);
+val = (l_uint8)(val * normh);
+SET_DATA_BYTE(lined, j, val);
+}
+for (j = wmwc; j < w; j++) {
+wn = wc + w - j;
+normw = (l_float32)fwc / (l_float32)wn;   /* > 1 */
+val = GET_DATA_BYTE(lined, j);
+val = (l_uint8)(val * normh * normw);
+SET_DATA_BYTE(lined, j, val);
+}
+}
+for (i = hc + 1; i < hmhc; i++) {    /* intermediate lines */
+lined = datad + wpl * i;
+for (j = 0; j <= wc; j++) {   /* first wc + 1 columns */
+wn = wc + j;
+normw = (l_float32)fwc / (l_float32)wn;   /* > 1 */
+val = GET_DATA_BYTE(lined, j);
+val = (l_uint8)(val * normw);
+SET_DATA_BYTE(lined, j, val);
+}
+for (j = wmwc; j < w; j++) {   /* last wc columns */
+wn = wc + w - j;
+normw = (l_float32)fwc / (l_float32)wn;   /* > 1 */
+val = GET_DATA_BYTE(lined, j);
+val = (l_uint8)(val * normw);
+SET_DATA_BYTE(lined, j, val);
+}
+}
+}
+/*----------------------------------------------------------------------*
+*                          Census transform                            *
+*----------------------------------------------------------------------*/
+/*!
+* \brief   pixCensusTransform()
+*
+* \param[in]    pixs       8 bpp
+* \param[in]    halfsize   of square over which neighbors are averaged
+* \param[in]    pixacc     [optional] 32 bpp pix
+* \return  pixd 1 bpp
+*
+* <pre>
+* Notes:
+*      (1) The Census transform was invented by Ramin Zabih and John Woodfill
+*          ("Non-parametric local transforms for computing visual
+*          correspondence", Third European Conference on Computer Vision,
+*          Stockholm, Sweden, May 1994); see publications at
+*             http://www.cs.cornell.edu/~rdz/index.htm
+*          This compares each pixel against the average of its neighbors,
+*          in a square of odd dimension centered on the pixel.
+*          If the pixel is greater than the average of its neighbors,
+*          the output pixel value is 1; otherwise it is 0.
+*      (2) This can be used as an encoding for an image that is
+*          fairly robust against slow illumination changes, with
+*          applications in image comparison and mosaicing.
+*      (3) The size of the convolution kernel is (2 * halfsize + 1)
+*          on a side.  The halfsize parameter must be >= 1.
+*      (4) If accum pix is null, make one, use it, and destroy it
+*          before returning; otherwise, just use the input accum pix
+* </pre>
+*/
+PIX *
+pixCensusTransform(PIX     *pixs,
+l_int32  halfsize,
+PIX     *pixacc)
+{
+l_int32    i, j, w, h, wpls, wplv, wpld;
+l_int32    vals, valv;
+l_uint32  *datas, *datav, *datad, *lines, *linev, *lined;
+PIX       *pixav, *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+if (pixGetDepth(pixs) != 8)
+return (PIX *)ERROR_PTR("pixs not 8 bpp", __func__, NULL);
+if (halfsize < 1)
+return (PIX *)ERROR_PTR("halfsize must be >= 1", __func__, NULL);
+/* Get the average of each pixel with its neighbors */
+if ((pixav = pixBlockconvGray(pixs, pixacc, halfsize, halfsize))
+== NULL)
+return (PIX *)ERROR_PTR("pixav not made", __func__, NULL);
+/* Subtract the pixel from the average, and then compare
+* the pixel value with the remaining average */
+pixGetDimensions(pixs, &w, &h, NULL);
+if ((pixd = pixCreate(w, h, 1)) == NULL) {
+pixDestroy(&pixav);
+return (PIX *)ERROR_PTR("pixd not made", __func__, NULL);
+}
+datas = pixGetData(pixs);
+datav = pixGetData(pixav);
+datad = pixGetData(pixd);
+wpls = pixGetWpl(pixs);
+wplv = pixGetWpl(pixav);
+wpld = pixGetWpl(pixd);
+for (i = 0; i < h; i++) {
+lines = datas + i * wpls;
+linev = datav + i * wplv;
+lined = datad + i * wpld;
+for (j = 0; j < w; j++) {
+vals = GET_DATA_BYTE(lines, j);
+valv = GET_DATA_BYTE(linev, j);
+if (vals > valv)
+SET_DATA_BIT(lined, j);
+}
+}
+pixDestroy(&pixav);
+return pixd;
+}
+/*----------------------------------------------------------------------*
+*                         Generic convolution                          *
+*----------------------------------------------------------------------*/
+/*!
+* \brief   pixConvolve()
+*
+* \param[in]    pixs       8, 16, 32 bpp; no colormap
+* \param[in]    kel        kernel
+* \param[in]    outdepth   of pixd: 8, 16 or 32
+* \param[in]    normflag   1 to normalize kernel to unit sum; 0 otherwise
+* \return  pixd 8, 16 or 32 bpp
+*
+* <pre>
+* Notes:
+*      (1) This gives a convolution with an arbitrary kernel.
+*      (2) The input pixs must have only one sample/pixel.
+*          To do a convolution on an RGB image, use pixConvolveRGB().
+*      (3) The parameter %outdepth determines the depth of the result.
+*          If the kernel is normalized to unit sum, the output values
+*          can never exceed 255, so an output depth of 8 bpp is sufficient.
+*          If the kernel is not normalized, it may be necessary to use
+*          16 or 32 bpp output to avoid overflow.
+*      (4) If normflag == 1, the result is normalized by scaling all
+*          kernel values for a unit sum.  If the sum of kernel values
+*          is very close to zero, the kernel can not be normalized and
+*          the convolution will not be performed.  A warning is issued.
+*      (5) The kernel values can be positive or negative, but the
+*          result for the convolution can only be stored as a positive
+*          number.  Consequently, if it goes negative, the choices are
+*          to clip to 0 or take the absolute value.  We're choosing
+*          to take the absolute value.  (Another possibility would be
+*          to output a second unsigned image for the negative values.)
+*          If you want to get a clipped result, or to keep the negative
+*          values in the result, use fpixConvolve(), with the
+*          converters in fpix2.c between pix and fpix.
+*      (6) This uses a mirrored border to avoid special casing on
+*          the boundaries.
+*      (7) To get a subsampled output, call l_setConvolveSampling().
+*          The time to make a subsampled output is reduced by the
+*          product of the sampling factors.
+*      (8) The function is slow, running at about 12 machine cycles for
+*          each pixel-op in the convolution.  For example, with a 3 GHz
+*          cpu, a 1 Mpixel grayscale image, and a kernel with
+*          (sx * sy) = 25 elements, the convolution takes about 100 msec.
+* </pre>
+*/
+PIX *
+pixConvolve(PIX       *pixs,
+L_KERNEL  *kel,
+l_int32    outdepth,
+l_int32    normflag)
+{
+l_int32    i, j, id, jd, k, m, w, h, d, wd, hd, sx, sy, cx, cy, wplt, wpld;
+l_int32    val;
+l_uint32  *datat, *datad, *linet, *lined;
+l_float32  sum;
+L_KERNEL  *keli, *keln;
+PIX       *pixt, *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+if (pixGetColormap(pixs))
+return (PIX *)ERROR_PTR("pixs has colormap", __func__, NULL);
+pixGetDimensions(pixs, &w, &h, &d);
+if (d != 8 && d != 16 && d != 32)
+return (PIX *)ERROR_PTR("pixs not 8, 16, or 32 bpp", __func__, NULL);
+if (!kel)
+return (PIX *)ERROR_PTR("kel not defined", __func__, NULL);
+pixd = NULL;
+keli = kernelInvert(kel);
+kernelGetParameters(keli, &sy, &sx, &cy, &cx);
+if (normflag)
+keln = kernelNormalize(keli, 1.0);
+else
+keln = kernelCopy(keli);
+if ((pixt = pixAddMirroredBorder(pixs, cx, sx - cx, cy, sy - cy)) == NULL) {
+L_ERROR("pixt not made\n", __func__);
+goto cleanup;
+}
+wd = (w + ConvolveSamplingFactX - 1) / ConvolveSamplingFactX;
+hd = (h + ConvolveSamplingFactY - 1) / ConvolveSamplingFactY;
+pixd = pixCreate(wd, hd, outdepth);
+datat = pixGetData(pixt);
+datad = pixGetData(pixd);
+wplt = pixGetWpl(pixt);
+wpld = pixGetWpl(pixd);
+for (i = 0, id = 0; id < hd; i += ConvolveSamplingFactY, id++) {
+lined = datad + id * wpld;
+for (j = 0, jd = 0; jd < wd; j += ConvolveSamplingFactX, jd++) {
+sum = 0.0;
+for (k = 0; k < sy; k++) {
+linet = datat + (i + k) * wplt;
+if (d == 8) {
+for (m = 0; m < sx; m++) {
+val = GET_DATA_BYTE(linet, j + m);
+sum += val * keln->data[k][m];
+}
+} else if (d == 16) {
+for (m = 0; m < sx; m++) {
+val = GET_DATA_TWO_BYTES(linet, j + m);
+sum += val * keln->data[k][m];
+}
+} else {  /* d == 32 */
+for (m = 0; m < sx; m++) {
+val = *(linet + j + m);
+sum += val * keln->data[k][m];
+}
+}
+}
+if (sum < 0.0) sum = -sum;  /* make it non-negative */
+if (outdepth == 8)
+SET_DATA_BYTE(lined, jd, (l_int32)(sum + 0.5));
+else if (outdepth == 16)
+SET_DATA_TWO_BYTES(lined, jd, (l_int32)(sum + 0.5));
+else  /* outdepth == 32 */
+*(lined + jd) = (l_uint32)(sum + 0.5);
+}
+}
+cleanup:
+kernelDestroy(&keli);
+kernelDestroy(&keln);
+pixDestroy(&pixt);
+return pixd;
+}
+/*!
+* \brief   pixConvolveSep()
+*
+* \param[in]    pixs       8, 16, 32 bpp; no colormap
+* \param[in]    kelx       x-dependent kernel
+* \param[in]    kely       y-dependent kernel
+* \param[in]    outdepth   of pixd: 8, 16 or 32
+* \param[in]    normflag   1 to normalize kernel to unit sum; 0 otherwise
+* \return  pixd    8, 16 or 32 bpp
+*
+* <pre>
+* Notes:
+*      (1) This does a convolution with a separable kernel that is
+*          is a sequence of convolutions in x and y.  The two
+*          one-dimensional kernel components must be input separately;
+*          the full kernel is the product of these components.
+*          The support for the full kernel is thus a rectangular region.
+*      (2) The input pixs must have only one sample/pixel.
+*          To do a convolution on an RGB image, use pixConvolveSepRGB().
+*      (3) The parameter %outdepth determines the depth of the result.
+*          If the kernel is normalized to unit sum, the output values
+*          can never exceed 255, so an output depth of 8 bpp is sufficient.
+*          If the kernel is not normalized, it may be necessary to use
+*          16 or 32 bpp output to avoid overflow.
+*      (2) The %normflag parameter is used as in pixConvolve().
+*      (4) The kernel values can be positive or negative, but the
+*          result for the convolution can only be stored as a positive
+*          number.  Consequently, if it goes negative, the choices are
+*          to clip to 0 or take the absolute value.  We're choosing
+*          the former for now.  Another possibility would be to output
+*          a second unsigned image for the negative values.
+*      (5) Warning: if you use l_setConvolveSampling() to get a
+*          subsampled output, and the sampling factor is larger than
+*          the kernel half-width, it is faster to use the non-separable
+*          version pixConvolve().  This is because the first convolution
+*          here must be done on every raster line, regardless of the
+*          vertical sampling factor.  If the sampling factor is smaller
+*          than kernel half-width, it's faster to use the separable
+*          convolution.
+*      (6) This uses mirrored borders to avoid special casing on
+*          the boundaries.
+* </pre>
+*/
+PIX *
+pixConvolveSep(PIX       *pixs,
+L_KERNEL  *kelx,
+L_KERNEL  *kely,
+l_int32    outdepth,
+l_int32    normflag)
+{
+l_int32    d, xfact, yfact;
+L_KERNEL  *kelxn, *kelyn;
+PIX       *pixt, *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+d = pixGetDepth(pixs);
+if (d != 8 && d != 16 && d != 32)
+return (PIX *)ERROR_PTR("pixs not 8, 16, or 32 bpp", __func__, NULL);
+if (!kelx)
+return (PIX *)ERROR_PTR("kelx not defined", __func__, NULL);
+if (!kely)
+return (PIX *)ERROR_PTR("kely not defined", __func__, NULL);
+xfact = ConvolveSamplingFactX;
+yfact = ConvolveSamplingFactY;
+if (normflag) {
+kelxn = kernelNormalize(kelx, 1000.0f);
+kelyn = kernelNormalize(kely, 0.001f);
+l_setConvolveSampling(xfact, 1);
+pixt = pixConvolve(pixs, kelxn, 32, 0);
+l_setConvolveSampling(1, yfact);
+pixd = pixConvolve(pixt, kelyn, outdepth, 0);
+l_setConvolveSampling(xfact, yfact);  /* restore */
+kernelDestroy(&kelxn);
+kernelDestroy(&kelyn);
+} else {  /* don't normalize */
+l_setConvolveSampling(xfact, 1);
+pixt = pixConvolve(pixs, kelx, 32, 0);
+l_setConvolveSampling(1, yfact);
+pixd = pixConvolve(pixt, kely, outdepth, 0);
+l_setConvolveSampling(xfact, yfact);
+}
+pixDestroy(&pixt);
+return pixd;
+}
+/*!
+* \brief   pixConvolveRGB()
+*
+* \param[in]    pixs   32 bpp rgb
+* \param[in]    kel    kernel
+* \return  pixd   32 bpp rgb
+*
+* <pre>
+* Notes:
+*      (1) This gives a convolution on an RGB image using an
+*          arbitrary kernel (which we normalize to keep each
+*          component within the range [0 ... 255].
+*      (2) The input pixs must be RGB.
+*      (3) The kernel values can be positive or negative, but the
+*          result for the convolution can only be stored as a positive
+*          number.  Consequently, if it goes negative, we clip the
+*          result to 0.
+*      (4) To get a subsampled output, call l_setConvolveSampling().
+*          The time to make a subsampled output is reduced by the
+*          product of the sampling factors.
+*      (5) This uses a mirrored border to avoid special casing on
+*          the boundaries.
+* </pre>
+*/
+PIX *
+pixConvolveRGB(PIX       *pixs,
+L_KERNEL  *kel)
+{
+PIX  *pixt, *pixr, *pixg, *pixb, *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+if (pixGetDepth(pixs) != 32)
+return (PIX *)ERROR_PTR("pixs is not 32 bpp", __func__, NULL);
+if (!kel)
+return (PIX *)ERROR_PTR("kel not defined", __func__, NULL);
+pixt = pixGetRGBComponent(pixs, COLOR_RED);
+pixr = pixConvolve(pixt, kel, 8, 1);
+pixDestroy(&pixt);
+pixt = pixGetRGBComponent(pixs, COLOR_GREEN);
+pixg = pixConvolve(pixt, kel, 8, 1);
+pixDestroy(&pixt);
+pixt = pixGetRGBComponent(pixs, COLOR_BLUE);
+pixb = pixConvolve(pixt, kel, 8, 1);
+pixDestroy(&pixt);
+pixd = pixCreateRGBImage(pixr, pixg, pixb);
+pixDestroy(&pixr);
+pixDestroy(&pixg);
+pixDestroy(&pixb);
+return pixd;
+}
+/*!
+* \brief   pixConvolveRGBSep()
+*
+* \param[in]    pixs   32 bpp rgb
+* \param[in]    kelx   x-dependent kernel
+* \param[in]    kely   y-dependent kernel
+* \return  pixd 32 bpp rgb
+*
+* <pre>
+* Notes:
+*      (1) This does a convolution on an RGB image using a separable
+*          kernel that is a sequence of convolutions in x and y.  The two
+*          one-dimensional kernel components must be input separately;
+*          the full kernel is the product of these components.
+*          The support for the full kernel is thus a rectangular region.
+*      (2) The kernel values can be positive or negative, but the
+*          result for the convolution can only be stored as a positive
+*          number.  Consequently, if it goes negative, we clip the
+*          result to 0.
+*      (3) To get a subsampled output, call l_setConvolveSampling().
+*          The time to make a subsampled output is reduced by the
+*          product of the sampling factors.
+*      (4) This uses a mirrored border to avoid special casing on
+*          the boundaries.
+* </pre>
+*/
+PIX *
+pixConvolveRGBSep(PIX       *pixs,
+L_KERNEL  *kelx,
+L_KERNEL  *kely)
+{
+PIX  *pixt, *pixr, *pixg, *pixb, *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+if (pixGetDepth(pixs) != 32)
+return (PIX *)ERROR_PTR("pixs is not 32 bpp", __func__, NULL);
+if (!kelx || !kely)
+return (PIX *)ERROR_PTR("kelx, kely not both defined", __func__, NULL);
+pixt = pixGetRGBComponent(pixs, COLOR_RED);
+pixr = pixConvolveSep(pixt, kelx, kely, 8, 1);
+pixDestroy(&pixt);
+pixt = pixGetRGBComponent(pixs, COLOR_GREEN);
+pixg = pixConvolveSep(pixt, kelx, kely, 8, 1);
+pixDestroy(&pixt);
+pixt = pixGetRGBComponent(pixs, COLOR_BLUE);
+pixb = pixConvolveSep(pixt, kelx, kely, 8, 1);
+pixDestroy(&pixt);
+pixd = pixCreateRGBImage(pixr, pixg, pixb);
+pixDestroy(&pixr);
+pixDestroy(&pixg);
+pixDestroy(&pixb);
+return pixd;
+}
+/*----------------------------------------------------------------------*
+*                  Generic convolution with float array                *
+*----------------------------------------------------------------------*/
+/*!
+* \brief   fpixConvolve()
+*
+* \param[in]    fpixs      32 bit float array
+* \param[in]    kel        kernel
+* \param[in]    normflag   1 to normalize kernel to unit sum; 0 otherwise
+* \return  fpixd 32 bit float array
+*
+* <pre>
+* Notes:
+*      (1) This gives a float convolution with an arbitrary kernel.
+*      (2) If normflag == 1, the result is normalized by scaling all
+*          kernel values for a unit sum.  If the sum of kernel values
+*          is very close to zero, the kernel can not be normalized and
+*          the convolution will not be performed.  A warning is issued.
+*      (3) With the FPix, there are no issues about negative
+*          array or kernel values.  The convolution is performed
+*          with single precision arithmetic.
+*      (4) To get a subsampled output, call l_setConvolveSampling().
+*          The time to make a subsampled output is reduced by the
+*          product of the sampling factors.
+*      (5) This uses a mirrored border to avoid special casing on
+*          the boundaries.
+* </pre>
+*/
+FPIX *
+fpixConvolve(FPIX      *fpixs,
+L_KERNEL  *kel,
+l_int32    normflag)
+{
+l_int32     i, j, id, jd, k, m, w, h, wd, hd, sx, sy, cx, cy, wplt, wpld;
+l_float32   val;
+l_float32  *datat, *datad, *linet, *lined;
+l_float32   sum;
+L_KERNEL   *keli, *keln;
+FPIX       *fpixt, *fpixd;
+if (!fpixs)
+return (FPIX *)ERROR_PTR("fpixs not defined", __func__, NULL);
+if (!kel)
+return (FPIX *)ERROR_PTR("kel not defined", __func__, NULL);
+fpixd = NULL;
+keli = kernelInvert(kel);
+kernelGetParameters(keli, &sy, &sx, &cy, &cx);
+if (normflag)
+keln = kernelNormalize(keli, 1.0);
+else
+keln = kernelCopy(keli);
+fpixGetDimensions(fpixs, &w, &h);
+fpixt = fpixAddMirroredBorder(fpixs, cx, sx - cx, cy, sy - cy);
+if (!fpixt) {
+L_ERROR("fpixt not made\n", __func__);
+goto cleanup;
+}
+wd = (w + ConvolveSamplingFactX - 1) / ConvolveSamplingFactX;
+hd = (h + ConvolveSamplingFactY - 1) / ConvolveSamplingFactY;
+fpixd = fpixCreate(wd, hd);
+datat = fpixGetData(fpixt);
+datad = fpixGetData(fpixd);
+wplt = fpixGetWpl(fpixt);
+wpld = fpixGetWpl(fpixd);
+for (i = 0, id = 0; id < hd; i += ConvolveSamplingFactY, id++) {
+lined = datad + id * wpld;
+for (j = 0, jd = 0; jd < wd; j += ConvolveSamplingFactX, jd++) {
+sum = 0.0;
+for (k = 0; k < sy; k++) {
+linet = datat + (i + k) * wplt;
+for (m = 0; m < sx; m++) {
+val = *(linet + j + m);
+sum += val * keln->data[k][m];
+}
+}
+*(lined + jd) = sum;
+}
+}
+cleanup:
+kernelDestroy(&keli);
+kernelDestroy(&keln);
+fpixDestroy(&fpixt);
+return fpixd;
+}
+/*!
+* \brief   fpixConvolveSep()
+*
+* \param[in]    fpixs      32 bit float array
+* \param[in]    kelx       x-dependent kernel
+* \param[in]    kely       y-dependent kernel
+* \param[in]    normflag   1 to normalize kernel to unit sum; 0 otherwise
+* \return  fpixd    32 bit float array
+*
+* <pre>
+* Notes:
+*      (1) This does a convolution with a separable kernel that is
+*          is a sequence of convolutions in x and y.  The two
+*          one-dimensional kernel components must be input separately;
+*          the full kernel is the product of these components.
+*          The support for the full kernel is thus a rectangular region.
+*      (2) The normflag parameter is used as in fpixConvolve().
+*      (3) Warning: if you use l_setConvolveSampling() to get a
+*          subsampled output, and the sampling factor is larger than
+*          the kernel half-width, it is faster to use the non-separable
+*          version pixConvolve().  This is because the first convolution
+*          here must be done on every raster line, regardless of the
+*          vertical sampling factor.  If the sampling factor is smaller
+*          than kernel half-width, it's faster to use the separable
+*          convolution.
+*      (4) This uses mirrored borders to avoid special casing on
+*          the boundaries.
+* </pre>
+*/
+FPIX *
+fpixConvolveSep(FPIX      *fpixs,
+L_KERNEL  *kelx,
+L_KERNEL  *kely,
+l_int32    normflag)
+{
+l_int32    xfact, yfact;
+L_KERNEL  *kelxn, *kelyn;
+FPIX      *fpixt, *fpixd;
+if (!fpixs)
+return (FPIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+if (!kelx)
+return (FPIX *)ERROR_PTR("kelx not defined", __func__, NULL);
+if (!kely)
+return (FPIX *)ERROR_PTR("kely not defined", __func__, NULL);
+xfact = ConvolveSamplingFactX;
+yfact = ConvolveSamplingFactY;
+if (normflag) {
+kelxn = kernelNormalize(kelx, 1.0);
+kelyn = kernelNormalize(kely, 1.0);
+l_setConvolveSampling(xfact, 1);
+fpixt = fpixConvolve(fpixs, kelxn, 0);
+l_setConvolveSampling(1, yfact);
+fpixd = fpixConvolve(fpixt, kelyn, 0);
+l_setConvolveSampling(xfact, yfact);  /* restore */
+kernelDestroy(&kelxn);
+kernelDestroy(&kelyn);
+} else {  /* don't normalize */
+l_setConvolveSampling(xfact, 1);
+fpixt = fpixConvolve(fpixs, kelx, 0);
+l_setConvolveSampling(1, yfact);
+fpixd = fpixConvolve(fpixt, kely, 0);
+l_setConvolveSampling(xfact, yfact);
+}
+fpixDestroy(&fpixt);
+return fpixd;
+}
+/*------------------------------------------------------------------------*
+*              Convolution with bias (for non-negative output)           *
+*------------------------------------------------------------------------*/
+/*!
+* \brief   pixConvolveWithBias()
+*
+* \param[in]    pixs     8 bpp; no colormap
+* \param[in]    kel1
+* \param[in]    kel2     can be null; use if separable
+* \param[in]    force8   if 1, force output to 8 bpp; otherwise, determine
+*                        output depth by the dynamic range of pixel values
+* \param[out]   pbias    applied bias
+* \return  pixd 8 or 16 bpp
+*
+* <pre>
+* Notes:
+*      (1) This does a convolution with either a single kernel or
+*          a pair of separable kernels, and automatically applies whatever
+*          bias (shift) is required so that the resulting pixel values
+*          are non-negative.
+*      (2) The kernel is always normalized.  If there are no negative
+*          values in the kernel, a standard normalized convolution is
+*          performed, with 8 bpp output.  If the sum of kernel values is
+*          very close to zero, the kernel can not be normalized and
+*          the convolution will not be performed.  An error message results.
+*      (3) If there are negative values in the kernel, the pix is
+*          converted to an fpix, the convolution is done on the fpix, and
+*          a bias (shift) may need to be applied.
+*      (4) If force8 == TRUE and the range of values after the convolution
+*          is > 255, the output values will be scaled to fit in [0 ... 255].
+*          If force8 == FALSE, the output will be either 8 or 16 bpp,
+*          to accommodate the dynamic range of output values without scaling.
+* </pre>
+*/
+PIX *
+pixConvolveWithBias(PIX       *pixs,
+L_KERNEL  *kel1,
+L_KERNEL  *kel2,
+l_int32    force8,
+l_int32   *pbias)
+{
+l_int32    outdepth;
+l_float32  min1, min2, min, minval, maxval, range;
+FPIX      *fpix1, *fpix2;
+PIX       *pixd;
+if (!pbias)
+return (PIX *)ERROR_PTR("&bias not defined", __func__, NULL);
+*pbias = 0;
+if (!pixs || pixGetDepth(pixs) != 8)
+return (PIX *)ERROR_PTR("pixs undefined or not 8 bpp", __func__, NULL);
+if (pixGetColormap(pixs))
+return (PIX *)ERROR_PTR("pixs has colormap", __func__, NULL);
+if (!kel1)
+return (PIX *)ERROR_PTR("kel1 not defined", __func__, NULL);
+/* Determine if negative values can be produced in the convolution */
+kernelGetMinMax(kel1, &min1, NULL);
+min2 = 0.0;
+if (kel2)
+kernelGetMinMax(kel2, &min2, NULL);
+min = L_MIN(min1, min2);
+if (min >= 0.0) {
+if (!kel2)
+return pixConvolve(pixs, kel1, 8, 1);
+else
+return pixConvolveSep(pixs, kel1, kel2, 8, 1);
+}
+/* Bias may need to be applied; convert to fpix and convolve */
+fpix1 = pixConvertToFPix(pixs, 1);
+if (!kel2)
+fpix2 = fpixConvolve(fpix1, kel1, 1);
+else
+fpix2 = fpixConvolveSep(fpix1, kel1, kel2, 1);
+fpixDestroy(&fpix1);
+/* Determine the bias and the dynamic range.
+* If the dynamic range is <= 255, just shift the values by the
+* bias, if any.
+* If the dynamic range is > 255, there are two cases:
+*    (1) the output depth is not forced to 8 bpp
+*           ==> apply the bias without scaling; outdepth = 16
+*    (2) the output depth is forced to 8
+*           ==> linearly map the pixel values to [0 ... 255].  */
+fpixGetMin(fpix2, &minval, NULL, NULL);
+fpixGetMax(fpix2, &maxval, NULL, NULL);
+range = maxval - minval;
+*pbias = (minval < 0.0) ? -minval : 0.0;
+fpixAddMultConstant(fpix2, *pbias, 1.0);  /* shift: min val ==> 0 */
+if (range <= 255 || !force8) {  /* no scaling of output values */
+outdepth = (range > 255) ? 16 : 8;
+} else {  /* scale output values to fit in 8 bpp */
+fpixAddMultConstant(fpix2, 0.0, (255.0 / range));
+outdepth = 8;
+}
+/* Convert back to pix; it won't do any clipping */
+pixd = fpixConvertToPix(fpix2, outdepth, L_CLIP_TO_ZERO, 0);
+fpixDestroy(&fpix2);
+return pixd;
+}
+/*------------------------------------------------------------------------*
+*                Set parameter for convolution subsampling               *
+*------------------------------------------------------------------------*/
+/*!
+* \brief   l_setConvolveSampling()
+*
+* \param[in]    xfact, yfact     integer >= 1
+* \return  void
+*
+* <pre>
+* Notes:
+*      (1) This sets the x and y output subsampling factors for generic pix
+*          and fpix convolution.  The default values are 1 (no subsampling).
+* </pre>
+*/
+void
+l_setConvolveSampling(l_int32  xfact,
+l_int32  yfact)
+{
+if (xfact < 1) xfact = 1;
+if (yfact < 1) yfact = 1;
+ConvolveSamplingFactX = xfact;
+ConvolveSamplingFactY = yfact;
+}
+/*------------------------------------------------------------------------*
+*                          Additive gaussian noise                       *
+*------------------------------------------------------------------------*/
+/*!
+* \brief   pixAddGaussianNoise()
+*
+* \param[in]    pixs     8 bpp gray or 32 bpp rgb; no colormap
+* \param[in]    stdev    of noise
+* \return  pixd    8 or 32 bpp, or NULL on error
+*
+* <pre>
+* Notes:
+*      (1) This adds noise to each pixel, taken from a normal
+*          distribution with zero mean and specified standard deviation.
+* </pre>
+*/
+PIX *
+pixAddGaussianNoise(PIX       *pixs,
+l_float32  stdev)
+{
+l_int32    i, j, w, h, d, wpls, wpld, val, rval, gval, bval;
+l_uint32   pixel;
+l_uint32  *datas, *datad, *lines, *lined;
+PIX       *pixd;
+if (!pixs)
+return (PIX *)ERROR_PTR("pixs not defined", __func__, NULL);
+if (pixGetColormap(pixs))
+return (PIX *)ERROR_PTR("pixs has colormap", __func__, NULL);
+pixGetDimensions(pixs, &w, &h, &d);
+if (d != 8 && d != 32)
+return (PIX *)ERROR_PTR("pixs not 8 or 32 bpp", __func__, NULL);
+pixd = pixCreateTemplate(pixs);
+datas = pixGetData(pixs);
+datad = pixGetData(pixd);
+wpls = pixGetWpl(pixs);
+wpld = pixGetWpl(pixd);
+for (i = 0; i < h; i++) {
+lines = datas + i * wpls;
+lined = datad + i * wpld;
+for (j = 0; j < w; j++) {
+if (d == 8) {
+val = GET_DATA_BYTE(lines, j);
+val += (l_int32)(stdev * gaussDistribSampling() + 0.5);
+val = L_MIN(255, L_MAX(0, val));
+SET_DATA_BYTE(lined, j, val);
+} else {  /* d = 32 */
+pixel = *(lines + j);
+extractRGBValues(pixel, &rval, &gval, &bval);
+rval += (l_int32)(stdev * gaussDistribSampling() + 0.5);
+rval = L_MIN(255, L_MAX(0, rval));
+gval += (l_int32)(stdev * gaussDistribSampling() + 0.5);
+gval = L_MIN(255, L_MAX(0, gval));
+bval += (l_int32)(stdev * gaussDistribSampling() + 0.5);
+bval = L_MIN(255, L_MAX(0, bval));
+composeRGBPixel(rval, gval, bval, lined + j);
+}
+}
+}
+return pixd;
+}
+/*!
+* \brief   gaussDistribSampling()
+*
+* \return   gaussian distributed variable with zero mean and unit stdev
+*
+* <pre>
+* Notes:
+*      (1) For an explanation of the Box-Muller method for generating
+*          a normally distributed random variable with zero mean and
+*          unit standard deviation, see Numerical Recipes in C,
+*          2nd edition, p. 288ff.
+*      (2) This can be called sequentially to get samples that can be
+*          used for adding noise to each pixel of an image, for example.
+* </pre>
+*/
+l_float32
+gaussDistribSampling(void)
+{
+static l_int32    select = 0;  /* flips between 0 and 1 on successive calls */
+static l_float32  saveval;
+l_float32         frand, xval, yval, rsq, factor;
+if (select == 0) {
+while (1) {  /* choose a point in a 2x2 square, centered at origin */
+frand = (l_float32)rand() / (l_float32)RAND_MAX;
+xval = 2.0 * frand - 1.0;
+frand = (l_float32)rand() / (l_float32)RAND_MAX;
+yval = 2.0 * frand - 1.0;
+rsq = xval * xval + yval * yval;
+if (rsq > 0.0 && rsq < 1.0)  /* point is inside the unit circle */
+break;
+}
+factor = sqrt(-2.0 * log(rsq) / rsq);
+saveval = xval * factor;
+select = 1;
+return yval * factor;
+}
+else {
+select = 0;
+return saveval;
+}
+}

Mercurial > hgrepos > Python2 > PyMuPDF

comparison mupdf-source/thirdparty/leptonica/src/convolve.c @ 2:b50eed0cc0ef upstream