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+++ b/mupdf-source/thirdparty/leptonica/src/bilateral.h	Mon Sep 15 11:43:07 2025 +0200
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+/*====================================================================*
+ -  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.
+ *====================================================================*/
+
+#ifndef  LEPTONICA_BILATERAL_H
+#define  LEPTONICA_BILATERAL_H
+
+/*!
+ * \file bilateral.h
+ *
+ * <pre>
+ *  Contains the following struct
+ *      struct L_Bilateral
+ *
+ *
+ *  For a tutorial introduction to bilateral filters, which apply a
+ *  gaussian blur to smooth parts of the image while preserving edges, see
+ *    http://people.csail.mit.edu/sparis/bf_course/slides/03_definition_bf.pdf
+ *
+ *  We give an implementation of a bilateral filtering algorithm given in:
+ *    "Real-Time O(1) Bilateral Filtering," by Yang, Tan and Ahuja, CVPR 2009
+ *  which is at:
+ *    http://vision.ai.uiuc.edu/~qyang6/publications/cvpr-09-qingxiong-yang.pdf
+ *  This is based on an earlier algorithm by Sylvain Paris and Frédo Durand:
+ *    http://people.csail.mit.edu/sparis/publi/2006/eccv/
+ *               Paris_06_Fast_Approximation.pdf
+ *
+ *  The kernel of the filter is a product of a spatial gaussian and a
+ *  monotonically decreasing function of the difference in intensity
+ *  between the source pixel and the neighboring pixel.  The intensity
+ *  part of the filter gives higher influence for pixels with intensities
+ *  that are near to the source pixel, and the spatial part of the
+ *  filter gives higher weight to pixels that are near the source pixel.
+ *  This combination smooths in relatively uniform regions, while
+ *  maintaining edges.
+ *
+ *  The advantage of the appoach of Yang et al is that it is separable,
+ *  so the computation time is linear in the gaussian filter size.
+ *  Furthermore, it is possible to do much of the computation as a reduced
+ *  scale, which gives a good approximation to the full resolution version
+ *  but greatly speeds it up.
+ *
+ *  The bilateral filtered value at x is:
+ *
+ *            sum[y in N(x)]: spatial(|y - x|) * range(|I(x) - I(y)|) * I(y)
+ *    I'(x) = --------------------------------------------------------------
+ *            sum[y in N(x)]: spatial(|y - x|) * range(|I(x) - I(y)|)
+ *
+ *  where I() is the input image, I'() is the filtered image, N(x) is the
+ *  set of pixels around x in the filter support, and spatial() and range()
+ *  are gaussian functions:
+ *          spatial(x) = exp(-x^2 / (2 * s_s^2))
+ *          range(x) = exp(-x^2 / (2 * s_r^2))
+ *  and s_s and s_r and the standard deviations of the two gaussians.
+ *
+ *  Yang et al use a separable approximation to this, by defining a set
+ *  of related but separable functions J(k,x), that we call Principal
+ *  Bilateral Components (PBC):
+ *
+ *             sum[y in N(x)]: spatial(|y - x|) * range(|k - I(y)|) * I(y)
+ *    J(k,x) = -----------------------------------------------------------
+ *             sum[y in N(x)]: spatial(|y - x|) * range(|k - I(y)|)
+ *
+ *  which are computed quickly for a set of n values k[p], p = 0 ... n-1.
+ *  Then each output pixel is found using a linear interpolation:
+ *
+ *    I'(x) = (1 - q) * J(k[p],x) + q * J(k[p+1],x)
+ *
+ *  where J(k[p],x) and J(k[p+1],x) are PBC for which
+ *    k[p] <= I(x) and k[p+1] >= I(x), and
+ *    q = (I(x) - k[p]) / (k[p+1] - k[p]).
+ *
+ *  We can also subsample I(x), create subsampled versions of J(k,x),
+ *  which are then interpolated between for I'(x).
+ *
+ *  We generate 'pixsc', by optionally downscaling the input image
+ *  (using area mapping by the factor 'reduction'), and then adding
+ *  a mirrored border to avoid boundary cases.  This is then used
+ *  to compute 'ncomps' PBCs.
+ *
+ *  The 'spatial_stdev' is also downscaled by 'reduction'.  The size
+ *  of the 'spatial' array is 4 * (reduced 'spatial_stdev') + 1.
+ *  The size of the 'range' array is 256.
+ * </pre>
+ */
+
+
+/*------------------------------------------------------------------------*
+ *                          Bilateral filter                              *
+ *------------------------------------------------------------------------*/
+
+/*! Bilateral filter */
+struct L_Bilateral
+{
+    struct Pix     *pixs;           /*!< clone of source pix                 */
+    struct Pix     *pixsc;          /*!< downscaled pix with mirrored border */
+    l_int32         reduction;      /*!< 1, 2 or 4x for intermediates        */
+    l_float32       spatial_stdev;  /*!< stdev of spatial gaussian           */
+    l_float32       range_stdev;    /*!< stdev of range gaussian             */
+    l_float32      *spatial;        /*!< 1D gaussian spatial kernel          */
+    l_float32      *range;          /*!< one-sided gaussian range kernel     */
+    l_int32         minval;         /*!< min value in 8 bpp pix              */
+    l_int32         maxval;         /*!< max value in 8 bpp pix              */
+    l_int32         ncomps;         /*!< number of intermediate results      */
+    l_int32        *nc;             /*!< set of k values (size ncomps)       */
+    l_int32        *kindex;         /*!< mapping from intensity to lower k   */
+    l_float32      *kfract;         /*!< mapping from intensity to fract k   */
+    struct Pixa    *pixac;          /*!< intermediate result images (PBC)    */
+    l_uint32     ***lineset;        /*!< lineptrs for pixac                  */
+};
+typedef struct L_Bilateral  L_BILATERAL;
+
+
+#endif  /* LEPTONICA_BILATERAL_H */