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comparison mupdf-source/thirdparty/lcms2/src/cmsgamma.c @ 2:b50eed0cc0ef upstream

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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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1:1d09e1dec1d9 2:b50eed0cc0ef
1 //---------------------------------------------------------------------------------
2 //
3 // Little Color Management System
4 // Copyright (c) 1998-2023 Marti Maria Saguer
5 //
6 // Permission is hereby granted, free of charge, to any person obtaining
7 // a copy of this software and associated documentation files (the "Software"),
8 // to deal in the Software without restriction, including without limitation
9 // the rights to use, copy, modify, merge, publish, distribute, sublicense,
10 // and/or sell copies of the Software, and to permit persons to whom the Software
11 // is furnished to do so, subject to the following conditions:
12 //
13 // The above copyright notice and this permission notice shall be included in
14 // all copies or substantial portions of the Software.
15 //
16 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
17 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
18 // THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
19 // NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
20 // LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
21 // OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
22 // WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
23 //
24 //---------------------------------------------------------------------------------
25 //
26 #include "lcms2_internal.h"
27
28 // Tone curves are powerful constructs that can contain curves specified in diverse ways.
29 // The curve is stored in segments, where each segment can be sampled or specified by parameters.
30 // a 16.bit simplification of the *whole* curve is kept for optimization purposes. For float operation,
31 // each segment is evaluated separately. Plug-ins may be used to define new parametric schemes,
32 // each plug-in may define up to MAX_TYPES_IN_LCMS_PLUGIN functions types. For defining a function,
33 // the plug-in should provide the type id, how many parameters each type has, and a pointer to
34 // a procedure that evaluates the function. In the case of reverse evaluation, the evaluator will
35 // be called with the type id as a negative value, and a sampled version of the reversed curve
36 // will be built.
37
38 // ----------------------------------------------------------------- Implementation
39 // Maxim number of nodes
40 #define MAX_NODES_IN_CURVE 4097
41 #define MINUS_INF (-1E22F)
42 #define PLUS_INF (+1E22F)
43
44 // The list of supported parametric curves
45 typedef struct _cmsParametricCurvesCollection_st {
46
47 cmsUInt32Number nFunctions; // Number of supported functions in this chunk
48 cmsInt32Number FunctionTypes[MAX_TYPES_IN_LCMS_PLUGIN]; // The identification types
49 cmsUInt32Number ParameterCount[MAX_TYPES_IN_LCMS_PLUGIN]; // Number of parameters for each function
50
51 cmsParametricCurveEvaluator Evaluator; // The evaluator
52
53 struct _cmsParametricCurvesCollection_st* Next; // Next in list
54
55 } _cmsParametricCurvesCollection;
56
57 // This is the default (built-in) evaluator
58 static cmsFloat64Number DefaultEvalParametricFn(cmsContext ContextID, cmsInt32Number Type, const cmsFloat64Number Params[], cmsFloat64Number R);
59
60 // The built-in list
61 static _cmsParametricCurvesCollection DefaultCurves = {
62 10, // # of curve types
63 { 1, 2, 3, 4, 5, 6, 7, 8, 108, 109 }, // Parametric curve ID
64 { 1, 3, 4, 5, 7, 4, 5, 5, 1, 1 }, // Parameters by type
65 DefaultEvalParametricFn, // Evaluator
66 NULL // Next in chain
67 };
68
69 // Duplicates the zone of memory used by the plug-in in the new context
70 static
71 void DupPluginCurvesList(struct _cmsContext_struct* ctx,
72 const struct _cmsContext_struct* src)
73 {
74 _cmsCurvesPluginChunkType newHead = { NULL };
75 _cmsParametricCurvesCollection* entry;
76 _cmsParametricCurvesCollection* Anterior = NULL;
77 _cmsCurvesPluginChunkType* head = (_cmsCurvesPluginChunkType*) src->chunks[CurvesPlugin];
78
79 _cmsAssert(head != NULL);
80
81 // Walk the list copying all nodes
82 for (entry = head->ParametricCurves;
83 entry != NULL;
84 entry = entry ->Next) {
85
86 _cmsParametricCurvesCollection *newEntry = ( _cmsParametricCurvesCollection *) _cmsSubAllocDup(ctx ->MemPool, entry, sizeof(_cmsParametricCurvesCollection));
87
88 if (newEntry == NULL)
89 return;
90
91 // We want to keep the linked list order, so this is a little bit tricky
92 newEntry -> Next = NULL;
93 if (Anterior)
94 Anterior -> Next = newEntry;
95
96 Anterior = newEntry;
97
98 if (newHead.ParametricCurves == NULL)
99 newHead.ParametricCurves = newEntry;
100 }
101
102 ctx ->chunks[CurvesPlugin] = _cmsSubAllocDup(ctx->MemPool, &newHead, sizeof(_cmsCurvesPluginChunkType));
103 }
104
105 // The allocator have to follow the chain
106 void _cmsAllocCurvesPluginChunk(struct _cmsContext_struct* ctx,
107 const struct _cmsContext_struct* src)
108 {
109 _cmsAssert(ctx != NULL);
110
111 if (src != NULL) {
112
113 // Copy all linked list
114 DupPluginCurvesList(ctx, src);
115 }
116 else {
117 static _cmsCurvesPluginChunkType CurvesPluginChunk = { NULL };
118 ctx ->chunks[CurvesPlugin] = _cmsSubAllocDup(ctx ->MemPool, &CurvesPluginChunk, sizeof(_cmsCurvesPluginChunkType));
119 }
120 }
121
122
123 // The linked list head
124 _cmsCurvesPluginChunkType _cmsCurvesPluginChunk = { NULL };
125
126 // As a way to install new parametric curves
127 cmsBool _cmsRegisterParametricCurvesPlugin(cmsContext ContextID, cmsPluginBase* Data)
128 {
129 _cmsCurvesPluginChunkType* ctx = ( _cmsCurvesPluginChunkType*) _cmsContextGetClientChunk(ContextID, CurvesPlugin);
130 cmsPluginParametricCurves* Plugin = (cmsPluginParametricCurves*) Data;
131 _cmsParametricCurvesCollection* fl;
132
133 if (Data == NULL) {
134
135 ctx -> ParametricCurves = NULL;
136 return TRUE;
137 }
138
139 fl = (_cmsParametricCurvesCollection*) _cmsPluginMalloc(ContextID, sizeof(_cmsParametricCurvesCollection));
140 if (fl == NULL) return FALSE;
141
142 // Copy the parameters
143 fl ->Evaluator = Plugin ->Evaluator;
144 fl ->nFunctions = Plugin ->nFunctions;
145
146 // Make sure no mem overwrites
147 if (fl ->nFunctions > MAX_TYPES_IN_LCMS_PLUGIN)
148 fl ->nFunctions = MAX_TYPES_IN_LCMS_PLUGIN;
149
150 // Copy the data
151 memmove(fl->FunctionTypes, Plugin ->FunctionTypes, fl->nFunctions * sizeof(cmsUInt32Number));
152 memmove(fl->ParameterCount, Plugin ->ParameterCount, fl->nFunctions * sizeof(cmsUInt32Number));
153
154 // Keep linked list
155 fl ->Next = ctx->ParametricCurves;
156 ctx->ParametricCurves = fl;
157
158 // All is ok
159 return TRUE;
160 }
161
162
163 // Search in type list, return position or -1 if not found
164 static
165 int IsInSet(int Type, _cmsParametricCurvesCollection* c)
166 {
167 int i;
168
169 for (i=0; i < (int) c ->nFunctions; i++)
170 if (abs(Type) == c ->FunctionTypes[i]) return i;
171
172 return -1;
173 }
174
175
176 // Search for the collection which contains a specific type
177 static
178 _cmsParametricCurvesCollection *GetParametricCurveByType(cmsContext ContextID, int Type, int* index)
179 {
180 _cmsParametricCurvesCollection* c;
181 int Position;
182 _cmsCurvesPluginChunkType* ctx = ( _cmsCurvesPluginChunkType*) _cmsContextGetClientChunk(ContextID, CurvesPlugin);
183
184 for (c = ctx->ParametricCurves; c != NULL; c = c ->Next) {
185
186 Position = IsInSet(Type, c);
187
188 if (Position != -1) {
189 if (index != NULL)
190 *index = Position;
191 return c;
192 }
193 }
194 // If none found, revert for defaults
195 for (c = &DefaultCurves; c != NULL; c = c ->Next) {
196
197 Position = IsInSet(Type, c);
198
199 if (Position != -1) {
200 if (index != NULL)
201 *index = Position;
202 return c;
203 }
204 }
205
206 return NULL;
207 }
208
209 // Low level allocate, which takes care of memory details. nEntries may be zero, and in this case
210 // no optimization curve is computed. nSegments may also be zero in the inverse case, where only the
211 // optimization curve is given. Both features simultaneously is an error
212 static
213 cmsToneCurve* AllocateToneCurveStruct(cmsContext ContextID, cmsUInt32Number nEntries,
214 cmsUInt32Number nSegments, const cmsCurveSegment* Segments,
215 const cmsUInt16Number* Values)
216 {
217 cmsToneCurve* p;
218 cmsUInt32Number i;
219
220 // We allow huge tables, which are then restricted for smoothing operations
221 if (nEntries > 65530) {
222 cmsSignalError(ContextID, cmsERROR_RANGE, "Couldn't create tone curve of more than 65530 entries");
223 return NULL;
224 }
225
226 if (nEntries == 0 && nSegments == 0) {
227 cmsSignalError(ContextID, cmsERROR_RANGE, "Couldn't create tone curve with zero segments and no table");
228 return NULL;
229 }
230
231 // Allocate all required pointers, etc.
232 p = (cmsToneCurve*) _cmsMallocZero(ContextID, sizeof(cmsToneCurve));
233 if (!p) return NULL;
234
235 // In this case, there are no segments
236 if (nSegments == 0) {
237 p ->Segments = NULL;
238 p ->Evals = NULL;
239 }
240 else {
241 p ->Segments = (cmsCurveSegment*) _cmsCalloc(ContextID, nSegments, sizeof(cmsCurveSegment));
242 if (p ->Segments == NULL) goto Error;
243
244 p ->Evals = (cmsParametricCurveEvaluator*) _cmsCalloc(ContextID, nSegments, sizeof(cmsParametricCurveEvaluator));
245 if (p ->Evals == NULL) goto Error;
246 }
247
248 p -> nSegments = nSegments;
249
250 // This 16-bit table contains a limited precision representation of the whole curve and is kept for
251 // increasing xput on certain operations.
252 if (nEntries == 0) {
253 p ->Table16 = NULL;
254 }
255 else {
256 p ->Table16 = (cmsUInt16Number*) _cmsCalloc(ContextID, nEntries, sizeof(cmsUInt16Number));
257 if (p ->Table16 == NULL) goto Error;
258 }
259
260 p -> nEntries = nEntries;
261
262 // Initialize members if requested
263 if (Values != NULL && (nEntries > 0)) {
264
265 for (i=0; i < nEntries; i++)
266 p ->Table16[i] = Values[i];
267 }
268
269 // Initialize the segments stuff. The evaluator for each segment is located and a pointer to it
270 // is placed in advance to maximize performance.
271 if (Segments != NULL && (nSegments > 0)) {
272
273 _cmsParametricCurvesCollection *c;
274
275 p ->SegInterp = (cmsInterpParams**) _cmsCalloc(ContextID, nSegments, sizeof(cmsInterpParams*));
276 if (p ->SegInterp == NULL) goto Error;
277
278 for (i=0; i < nSegments; i++) {
279
280 // Type 0 is a special marker for table-based curves
281 if (Segments[i].Type == 0)
282 p ->SegInterp[i] = _cmsComputeInterpParams(ContextID, Segments[i].nGridPoints, 1, 1, NULL, CMS_LERP_FLAGS_FLOAT);
283
284 memmove(&p ->Segments[i], &Segments[i], sizeof(cmsCurveSegment));
285
286 if (Segments[i].Type == 0 && Segments[i].SampledPoints != NULL)
287 p ->Segments[i].SampledPoints = (cmsFloat32Number*) _cmsDupMem(ContextID, Segments[i].SampledPoints, sizeof(cmsFloat32Number) * Segments[i].nGridPoints);
288 else
289 p ->Segments[i].SampledPoints = NULL;
290
291
292 c = GetParametricCurveByType(ContextID, Segments[i].Type, NULL);
293 if (c != NULL)
294 p ->Evals[i] = c ->Evaluator;
295 }
296 }
297
298 p ->InterpParams = _cmsComputeInterpParams(ContextID, p ->nEntries, 1, 1, p->Table16, CMS_LERP_FLAGS_16BITS);
299 if (p->InterpParams != NULL)
300 return p;
301
302 Error:
303 for (i=0; i < nSegments; i++) {
304 if (p ->Segments && p ->Segments[i].SampledPoints) _cmsFree(ContextID, p ->Segments[i].SampledPoints);
305 if (p ->SegInterp && p ->SegInterp[i]) _cmsFree(ContextID, p ->SegInterp[i]);
306 }
307 if (p -> SegInterp) _cmsFree(ContextID, p -> SegInterp);
308 if (p -> Segments) _cmsFree(ContextID, p -> Segments);
309 if (p -> Evals) _cmsFree(ContextID, p -> Evals);
310 if (p ->Table16) _cmsFree(ContextID, p ->Table16);
311 _cmsFree(ContextID, p);
312 return NULL;
313 }
314
315
316 // Generates a sigmoidal function with desired steepness.
317 cmsINLINE double sigmoid_base(double k, double t)
318 {
319 return (1.0 / (1.0 + exp(-k * t))) - 0.5;
320 }
321
322 cmsINLINE double inverted_sigmoid_base(double k, double t)
323 {
324 return -log((1.0 / (t + 0.5)) - 1.0) / k;
325 }
326
327 cmsINLINE double sigmoid_factory(double k, double t)
328 {
329 double correction = 0.5 / sigmoid_base(k, 1);
330
331 return correction * sigmoid_base(k, 2.0 * t - 1.0) + 0.5;
332 }
333
334 cmsINLINE double inverse_sigmoid_factory(double k, double t)
335 {
336 double correction = 0.5 / sigmoid_base(k, 1);
337
338 return (inverted_sigmoid_base(k, (t - 0.5) / correction) + 1.0) / 2.0;
339 }
340
341
342 // Parametric Fn using floating point
343 static
344 cmsFloat64Number DefaultEvalParametricFn(cmsContext ContextID, cmsInt32Number Type, const cmsFloat64Number Params[], cmsFloat64Number R)
345 {
346 cmsFloat64Number e, Val, disc;
347 cmsUNUSED_PARAMETER(ContextID);
348
349 switch (Type) {
350
351 // X = Y ^ Gamma
352 case 1:
353 if (R < 0) {
354
355 if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE)
356 Val = R;
357 else
358 Val = 0;
359 }
360 else
361 Val = pow(R, Params[0]);
362 break;
363
364 // Type 1 Reversed: X = Y ^1/gamma
365 case -1:
366 if (R < 0) {
367
368 if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE)
369 Val = R;
370 else
371 Val = 0;
372 }
373 else
374 {
375 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE)
376 Val = PLUS_INF;
377 else
378 Val = pow(R, 1 / Params[0]);
379 }
380 break;
381
382 // CIE 122-1966
383 // Y = (aX + b)^Gamma | X >= -b/a
384 // Y = 0 | else
385 case 2:
386 {
387
388 if (fabs(Params[1]) < MATRIX_DET_TOLERANCE)
389 {
390 Val = 0;
391 }
392 else
393 {
394 disc = -Params[2] / Params[1];
395
396 if (R >= disc) {
397
398 e = Params[1] * R + Params[2];
399
400 if (e > 0)
401 Val = pow(e, Params[0]);
402 else
403 Val = 0;
404 }
405 else
406 Val = 0;
407 }
408 }
409 break;
410
411 // Type 2 Reversed
412 // X = (Y ^1/g - b) / a
413 case -2:
414 {
415 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
416 fabs(Params[1]) < MATRIX_DET_TOLERANCE)
417 {
418 Val = 0;
419 }
420 else
421 {
422 if (R < 0)
423 Val = 0;
424 else
425 Val = (pow(R, 1.0 / Params[0]) - Params[2]) / Params[1];
426
427 if (Val < 0)
428 Val = 0;
429 }
430 }
431 break;
432
433
434 // IEC 61966-3
435 // Y = (aX + b)^Gamma + c | X <= -b/a
436 // Y = c | else
437 case 3:
438 {
439 if (fabs(Params[1]) < MATRIX_DET_TOLERANCE)
440 {
441 Val = 0;
442 }
443 else
444 {
445 disc = -Params[2] / Params[1];
446 if (disc < 0)
447 disc = 0;
448
449 if (R >= disc) {
450
451 e = Params[1] * R + Params[2];
452
453 if (e > 0)
454 Val = pow(e, Params[0]) + Params[3];
455 else
456 Val = 0;
457 }
458 else
459 Val = Params[3];
460 }
461 }
462 break;
463
464
465 // Type 3 reversed
466 // X=((Y-c)^1/g - b)/a | (Y>=c)
467 // X=-b/a | (Y<c)
468 case -3:
469 {
470 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
471 fabs(Params[1]) < MATRIX_DET_TOLERANCE)
472 {
473 Val = 0;
474 }
475 else
476 {
477 if (R >= Params[3]) {
478
479 e = R - Params[3];
480
481 if (e > 0)
482 Val = (pow(e, 1 / Params[0]) - Params[2]) / Params[1];
483 else
484 Val = 0;
485 }
486 else {
487 Val = -Params[2] / Params[1];
488 }
489 }
490 }
491 break;
492
493
494 // IEC 61966-2.1 (sRGB)
495 // Y = (aX + b)^Gamma | X >= d
496 // Y = cX | X < d
497 case 4:
498 if (R >= Params[4]) {
499
500 e = Params[1]*R + Params[2];
501
502 if (e > 0)
503 Val = pow(e, Params[0]);
504 else
505 Val = 0;
506 }
507 else
508 Val = R * Params[3];
509 break;
510
511 // Type 4 reversed
512 // X=((Y^1/g-b)/a) | Y >= (ad+b)^g
513 // X=Y/c | Y< (ad+b)^g
514 case -4:
515 {
516
517 e = Params[1] * Params[4] + Params[2];
518 if (e < 0)
519 disc = 0;
520 else
521 disc = pow(e, Params[0]);
522
523 if (R >= disc) {
524
525 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
526 fabs(Params[1]) < MATRIX_DET_TOLERANCE)
527
528 Val = 0;
529
530 else
531 Val = (pow(R, 1.0 / Params[0]) - Params[2]) / Params[1];
532 }
533 else {
534
535 if (fabs(Params[3]) < MATRIX_DET_TOLERANCE)
536 Val = 0;
537 else
538 Val = R / Params[3];
539 }
540
541 }
542 break;
543
544
545 // Y = (aX + b)^Gamma + e | X >= d
546 // Y = cX + f | X < d
547 case 5:
548 if (R >= Params[4]) {
549
550 e = Params[1]*R + Params[2];
551
552 if (e > 0)
553 Val = pow(e, Params[0]) + Params[5];
554 else
555 Val = Params[5];
556 }
557 else
558 Val = R*Params[3] + Params[6];
559 break;
560
561
562 // Reversed type 5
563 // X=((Y-e)1/g-b)/a | Y >=(ad+b)^g+e), cd+f
564 // X=(Y-f)/c | else
565 case -5:
566 {
567 disc = Params[3] * Params[4] + Params[6];
568 if (R >= disc) {
569
570 e = R - Params[5];
571 if (e < 0)
572 Val = 0;
573 else
574 {
575 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
576 fabs(Params[1]) < MATRIX_DET_TOLERANCE)
577
578 Val = 0;
579 else
580 Val = (pow(e, 1.0 / Params[0]) - Params[2]) / Params[1];
581 }
582 }
583 else {
584 if (fabs(Params[3]) < MATRIX_DET_TOLERANCE)
585 Val = 0;
586 else
587 Val = (R - Params[6]) / Params[3];
588 }
589
590 }
591 break;
592
593
594 // Types 6,7,8 comes from segmented curves as described in ICCSpecRevision_02_11_06_Float.pdf
595 // Type 6 is basically identical to type 5 without d
596
597 // Y = (a * X + b) ^ Gamma + c
598 case 6:
599 e = Params[1]*R + Params[2];
600
601 // On gamma 1.0, don't clamp
602 if (Params[0] == 1.0) {
603 Val = e + Params[3];
604 }
605 else {
606 if (e < 0)
607 Val = Params[3];
608 else
609 Val = pow(e, Params[0]) + Params[3];
610 }
611 break;
612
613 // ((Y - c) ^1/Gamma - b) / a
614 case -6:
615 {
616 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
617 fabs(Params[1]) < MATRIX_DET_TOLERANCE)
618 {
619 Val = 0;
620 }
621 else
622 {
623 e = R - Params[3];
624 if (e < 0)
625 Val = 0;
626 else
627 Val = (pow(e, 1.0 / Params[0]) - Params[2]) / Params[1];
628 }
629 }
630 break;
631
632
633 // Y = a * log (b * X^Gamma + c) + d
634 case 7:
635
636 e = Params[2] * pow(R, Params[0]) + Params[3];
637 if (e <= 0)
638 Val = Params[4];
639 else
640 Val = Params[1]*log10(e) + Params[4];
641 break;
642
643 // (Y - d) / a = log(b * X ^Gamma + c)
644 // pow(10, (Y-d) / a) = b * X ^Gamma + c
645 // pow((pow(10, (Y-d) / a) - c) / b, 1/g) = X
646 case -7:
647 {
648 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
649 fabs(Params[1]) < MATRIX_DET_TOLERANCE ||
650 fabs(Params[2]) < MATRIX_DET_TOLERANCE)
651 {
652 Val = 0;
653 }
654 else
655 {
656 Val = pow((pow(10.0, (R - Params[4]) / Params[1]) - Params[3]) / Params[2], 1.0 / Params[0]);
657 }
658 }
659 break;
660
661
662 //Y = a * b^(c*X+d) + e
663 case 8:
664 Val = (Params[0] * pow(Params[1], Params[2] * R + Params[3]) + Params[4]);
665 break;
666
667
668 // Y = (log((y-e) / a) / log(b) - d ) / c
669 // a=0, b=1, c=2, d=3, e=4,
670 case -8:
671
672 disc = R - Params[4];
673 if (disc < 0) Val = 0;
674 else
675 {
676 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
677 fabs(Params[2]) < MATRIX_DET_TOLERANCE)
678 {
679 Val = 0;
680 }
681 else
682 {
683 Val = (log(disc / Params[0]) / log(Params[1]) - Params[3]) / Params[2];
684 }
685 }
686 break;
687
688
689 // S-Shaped: (1 - (1-x)^1/g)^1/g
690 case 108:
691 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE)
692 Val = 0;
693 else
694 Val = pow(1.0 - pow(1 - R, 1/Params[0]), 1/Params[0]);
695 break;
696
697 // y = (1 - (1-x)^1/g)^1/g
698 // y^g = (1 - (1-x)^1/g)
699 // 1 - y^g = (1-x)^1/g
700 // (1 - y^g)^g = 1 - x
701 // 1 - (1 - y^g)^g
702 case -108:
703 Val = 1 - pow(1 - pow(R, Params[0]), Params[0]);
704 break;
705
706 // Sigmoidals
707 case 109:
708 Val = sigmoid_factory(Params[0], R);
709 break;
710
711 case -109:
712 Val = inverse_sigmoid_factory(Params[0], R);
713 break;
714
715 default:
716 // Unsupported parametric curve. Should never reach here
717 return 0;
718 }
719
720 return Val;
721 }
722
723 // Evaluate a segmented function for a single value. Return -Inf if no valid segment found .
724 // If fn type is 0, perform an interpolation on the table
725 static
726 cmsFloat64Number EvalSegmentedFn(cmsContext ContextID, const cmsToneCurve *g, cmsFloat64Number R)
727 {
728 int i;
729 cmsFloat32Number Out32;
730 cmsFloat64Number Out;
731
732 for (i = (int) g->nSegments - 1; i >= 0; --i) {
733
734 // Check for domain
735 if ((R > g->Segments[i].x0) && (R <= g->Segments[i].x1)) {
736
737 // Type == 0 means segment is sampled
738 if (g->Segments[i].Type == 0) {
739
740 cmsFloat32Number R1 = (cmsFloat32Number)(R - g->Segments[i].x0) / (g->Segments[i].x1 - g->Segments[i].x0);
741
742 // Setup the table (TODO: clean that)
743 g->SegInterp[i]->Table = g->Segments[i].SampledPoints;
744
745 g->SegInterp[i]->Interpolation.LerpFloat(ContextID, &R1, &Out32, g->SegInterp[i]);
746 Out = (cmsFloat64Number) Out32;
747
748 }
749 else {
750 Out = g->Evals[i](ContextID, g->Segments[i].Type, g->Segments[i].Params, R);
751 }
752
753 if (isinf(Out))
754 return PLUS_INF;
755 else
756 {
757 if (isinf(-Out))
758 return MINUS_INF;
759 }
760
761 return Out;
762 }
763 }
764
765 return MINUS_INF;
766 }
767
768 // Access to estimated low-res table
769 cmsUInt32Number CMSEXPORT cmsGetToneCurveEstimatedTableEntries(cmsContext ContextID, const cmsToneCurve* t)
770 {
771 cmsUNUSED_PARAMETER(ContextID);
772 _cmsAssert(t != NULL);
773 return t ->nEntries;
774 }
775
776 const cmsUInt16Number* CMSEXPORT cmsGetToneCurveEstimatedTable(cmsContext ContextID, const cmsToneCurve* t)
777 {
778 cmsUNUSED_PARAMETER(ContextID);
779 _cmsAssert(t != NULL);
780 return t ->Table16;
781 }
782
783
784 // Create an empty gamma curve, by using tables. This specifies only the limited-precision part, and leaves the
785 // floating point description empty.
786 cmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurve16(cmsContext ContextID, cmsUInt32Number nEntries, const cmsUInt16Number Values[])
787 {
788 return AllocateToneCurveStruct(ContextID, nEntries, 0, NULL, Values);
789 }
790
791 static
792 cmsUInt32Number EntriesByGamma(cmsFloat64Number Gamma)
793 {
794 if (fabs(Gamma - 1.0) < 0.001) return 2;
795 return 4096;
796 }
797
798
799 // Create a segmented gamma, fill the table
800 cmsToneCurve* CMSEXPORT cmsBuildSegmentedToneCurve(cmsContext ContextID,
801 cmsUInt32Number nSegments, const cmsCurveSegment Segments[])
802 {
803 cmsUInt32Number i;
804 cmsFloat64Number R, Val;
805 cmsToneCurve* g;
806 cmsUInt32Number nGridPoints = 4096;
807
808 _cmsAssert(Segments != NULL);
809
810 // Optimizatin for identity curves.
811 if (nSegments == 1 && Segments[0].Type == 1) {
812
813 nGridPoints = EntriesByGamma(Segments[0].Params[0]);
814 }
815
816 g = AllocateToneCurveStruct(ContextID, nGridPoints, nSegments, Segments, NULL);
817 if (g == NULL) return NULL;
818
819 // Once we have the floating point version, we can approximate a 16 bit table of 4096 entries
820 // for performance reasons. This table would normally not be used except on 8/16 bits transforms.
821 for (i = 0; i < nGridPoints; i++) {
822
823 R = (cmsFloat64Number) i / (nGridPoints-1);
824
825 Val = EvalSegmentedFn(ContextID, g, R);
826
827 // Round and saturate
828 g ->Table16[i] = _cmsQuickSaturateWord(Val * 65535.0);
829 }
830
831 return g;
832 }
833
834 // Use a segmented curve to store the floating point table
835 cmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurveFloat(cmsContext ContextID, cmsUInt32Number nEntries, const cmsFloat32Number values[])
836 {
837 cmsCurveSegment Seg[3];
838
839 // Do some housekeeping
840 if (nEntries == 0 || values == NULL)
841 return NULL;
842
843 // A segmented tone curve should have function segments in the first and last positions
844 // Initialize segmented curve part up to 0 to constant value = samples[0]
845 Seg[0].x0 = MINUS_INF;
846 Seg[0].x1 = 0;
847 Seg[0].Type = 6;
848
849 Seg[0].Params[0] = 1;
850 Seg[0].Params[1] = 0;
851 Seg[0].Params[2] = 0;
852 Seg[0].Params[3] = values[0];
853 Seg[0].Params[4] = 0;
854
855 // From zero to 1
856 Seg[1].x0 = 0;
857 Seg[1].x1 = 1.0;
858 Seg[1].Type = 0;
859
860 Seg[1].nGridPoints = nEntries;
861 Seg[1].SampledPoints = (cmsFloat32Number*) values;
862
863 // Final segment is constant = lastsample
864 Seg[2].x0 = 1.0;
865 Seg[2].x1 = PLUS_INF;
866 Seg[2].Type = 6;
867
868 Seg[2].Params[0] = 1;
869 Seg[2].Params[1] = 0;
870 Seg[2].Params[2] = 0;
871 Seg[2].Params[3] = values[nEntries-1];
872 Seg[2].Params[4] = 0;
873
874
875 return cmsBuildSegmentedToneCurve(ContextID, 3, Seg);
876 }
877
878 // Parametric curves
879 //
880 // Parameters goes as: Curve, a, b, c, d, e, f
881 // Type is the ICC type +1
882 // if type is negative, then the curve is analytically inverted
883 cmsToneCurve* CMSEXPORT cmsBuildParametricToneCurve(cmsContext ContextID, cmsInt32Number Type, const cmsFloat64Number Params[])
884 {
885 cmsCurveSegment Seg0;
886 int Pos = 0;
887 cmsUInt32Number size;
888 _cmsParametricCurvesCollection* c = GetParametricCurveByType(ContextID, Type, &Pos);
889
890 _cmsAssert(Params != NULL);
891
892 if (c == NULL) {
893 cmsSignalError(ContextID, cmsERROR_UNKNOWN_EXTENSION, "Invalid parametric curve type %d", Type);
894 return NULL;
895 }
896
897 memset(&Seg0, 0, sizeof(Seg0));
898
899 Seg0.x0 = MINUS_INF;
900 Seg0.x1 = PLUS_INF;
901 Seg0.Type = Type;
902
903 size = c->ParameterCount[Pos] * sizeof(cmsFloat64Number);
904 memmove(Seg0.Params, Params, size);
905
906 return cmsBuildSegmentedToneCurve(ContextID, 1, &Seg0);
907 }
908
909
910
911 // Build a gamma table based on gamma constant
912 cmsToneCurve* CMSEXPORT cmsBuildGamma(cmsContext ContextID, cmsFloat64Number Gamma)
913 {
914 return cmsBuildParametricToneCurve(ContextID, 1, &Gamma);
915 }
916
917
918 // Free all memory taken by the gamma curve
919 void CMSEXPORT cmsFreeToneCurve(cmsContext ContextID, cmsToneCurve* Curve)
920 {
921 if (Curve == NULL) return;
922
923 _cmsFreeInterpParams(ContextID, Curve ->InterpParams);
924
925 if (Curve -> Table16)
926 _cmsFree(ContextID, Curve ->Table16);
927
928 if (Curve ->Segments) {
929
930 cmsUInt32Number i;
931
932 for (i=0; i < Curve ->nSegments; i++) {
933
934 if (Curve ->Segments[i].SampledPoints) {
935 _cmsFree(ContextID, Curve ->Segments[i].SampledPoints);
936 }
937
938 if (Curve ->SegInterp[i] != 0)
939 _cmsFreeInterpParams(ContextID, Curve->SegInterp[i]);
940 }
941
942 _cmsFree(ContextID, Curve ->Segments);
943 _cmsFree(ContextID, Curve ->SegInterp);
944 }
945
946 if (Curve -> Evals)
947 _cmsFree(ContextID, Curve -> Evals);
948
949 _cmsFree(ContextID, Curve);
950 }
951
952 // Utility function, free 3 gamma tables
953 void CMSEXPORT cmsFreeToneCurveTriple(cmsContext ContextID, cmsToneCurve* Curve[3])
954 {
955
956 _cmsAssert(Curve != NULL);
957
958 if (Curve[0] != NULL) cmsFreeToneCurve(ContextID, Curve[0]);
959 if (Curve[1] != NULL) cmsFreeToneCurve(ContextID, Curve[1]);
960 if (Curve[2] != NULL) cmsFreeToneCurve(ContextID, Curve[2]);
961
962 Curve[0] = Curve[1] = Curve[2] = NULL;
963 }
964
965
966 // Duplicate a gamma table
967 cmsToneCurve* CMSEXPORT cmsDupToneCurve(cmsContext ContextID, const cmsToneCurve* In)
968 {
969 if (In == NULL) return NULL;
970
971 return AllocateToneCurveStruct(ContextID, In ->nEntries, In ->nSegments, In ->Segments, In ->Table16);
972 }
973
974 // Joins two curves for X and Y. Curves should be monotonic.
975 // We want to get
976 //
977 // y = Y^-1(X(t))
978 //
979 cmsToneCurve* CMSEXPORT cmsJoinToneCurve(cmsContext ContextID,
980 const cmsToneCurve* X,
981 const cmsToneCurve* Y, cmsUInt32Number nResultingPoints)
982 {
983 cmsToneCurve* out = NULL;
984 cmsToneCurve* Yreversed = NULL;
985 cmsFloat32Number t, x;
986 cmsFloat32Number* Res = NULL;
987 cmsUInt32Number i;
988
989
990 _cmsAssert(X != NULL);
991 _cmsAssert(Y != NULL);
992
993 Yreversed = cmsReverseToneCurveEx(ContextID, nResultingPoints, Y);
994 if (Yreversed == NULL) goto Error;
995
996 Res = (cmsFloat32Number*) _cmsCalloc(ContextID, nResultingPoints, sizeof(cmsFloat32Number));
997 if (Res == NULL) goto Error;
998
999 //Iterate
1000 for (i=0; i < nResultingPoints; i++) {
1001
1002 t = (cmsFloat32Number) i / (cmsFloat32Number)(nResultingPoints-1);
1003 x = cmsEvalToneCurveFloat(ContextID, X, t);
1004 Res[i] = cmsEvalToneCurveFloat(ContextID, Yreversed, x);
1005 }
1006
1007 // Allocate space for output
1008 out = cmsBuildTabulatedToneCurveFloat(ContextID, nResultingPoints, Res);
1009
1010 Error:
1011
1012 if (Res != NULL) _cmsFree(ContextID, Res);
1013 if (Yreversed != NULL) cmsFreeToneCurve(ContextID, Yreversed);
1014
1015 return out;
1016 }
1017
1018
1019
1020 // Get the surrounding nodes. This is tricky on non-monotonic tables
1021 static
1022 int GetInterval(cmsFloat64Number In, const cmsUInt16Number LutTable[], const struct _cms_interp_struc* p)
1023 {
1024 int i;
1025 int y0, y1;
1026
1027 // A 1 point table is not allowed
1028 if (p -> Domain[0] < 1) return -1;
1029
1030 // Let's see if ascending or descending.
1031 if (LutTable[0] < LutTable[p ->Domain[0]]) {
1032
1033 // Table is overall ascending
1034 for (i = (int) p->Domain[0] - 1; i >= 0; --i) {
1035
1036 y0 = LutTable[i];
1037 y1 = LutTable[i+1];
1038
1039 if (y0 <= y1) { // Increasing
1040 if (In >= y0 && In <= y1) return i;
1041 }
1042 else
1043 if (y1 < y0) { // Decreasing
1044 if (In >= y1 && In <= y0) return i;
1045 }
1046 }
1047 }
1048 else {
1049 // Table is overall descending
1050 for (i=0; i < (int) p -> Domain[0]; i++) {
1051
1052 y0 = LutTable[i];
1053 y1 = LutTable[i+1];
1054
1055 if (y0 <= y1) { // Increasing
1056 if (In >= y0 && In <= y1) return i;
1057 }
1058 else
1059 if (y1 < y0) { // Decreasing
1060 if (In >= y1 && In <= y0) return i;
1061 }
1062 }
1063 }
1064
1065 return -1;
1066 }
1067
1068 // Reverse a gamma table
1069 cmsToneCurve* CMSEXPORT cmsReverseToneCurveEx(cmsContext ContextID, cmsUInt32Number nResultSamples, const cmsToneCurve* InCurve)
1070 {
1071 cmsToneCurve *out;
1072 cmsFloat64Number a = 0, b = 0, y, x1, y1, x2, y2;
1073 int i, j;
1074 int Ascending;
1075
1076 _cmsAssert(InCurve != NULL);
1077
1078 // Try to reverse it analytically whatever possible
1079
1080 if (InCurve ->nSegments == 1 && InCurve ->Segments[0].Type > 0 &&
1081 /* InCurve -> Segments[0].Type <= 5 */
1082 GetParametricCurveByType(ContextID, InCurve ->Segments[0].Type, NULL) != NULL) {
1083
1084 return cmsBuildParametricToneCurve(ContextID,
1085 -(InCurve -> Segments[0].Type),
1086 InCurve -> Segments[0].Params);
1087 }
1088
1089 // Nope, reverse the table.
1090 out = cmsBuildTabulatedToneCurve16(ContextID, nResultSamples, NULL);
1091 if (out == NULL)
1092 return NULL;
1093
1094 // We want to know if this is an ascending or descending table
1095 Ascending = !cmsIsToneCurveDescending(ContextID, InCurve);
1096
1097 // Iterate across Y axis
1098 for (i=0; i < (int) nResultSamples; i++) {
1099
1100 y = (cmsFloat64Number) i * 65535.0 / (nResultSamples - 1);
1101
1102 // Find interval in which y is within.
1103 j = GetInterval(y, InCurve->Table16, InCurve->InterpParams);
1104 if (j >= 0) {
1105
1106
1107 // Get limits of interval
1108 x1 = InCurve ->Table16[j];
1109 x2 = InCurve ->Table16[j+1];
1110
1111 y1 = (cmsFloat64Number) (j * 65535.0) / (InCurve ->nEntries - 1);
1112 y2 = (cmsFloat64Number) ((j+1) * 65535.0 ) / (InCurve ->nEntries - 1);
1113
1114 // If collapsed, then use any
1115 if (x1 == x2) {
1116
1117 out ->Table16[i] = _cmsQuickSaturateWord(Ascending ? y2 : y1);
1118 continue;
1119
1120 } else {
1121
1122 // Interpolate
1123 a = (y2 - y1) / (x2 - x1);
1124 b = y2 - a * x2;
1125 }
1126 }
1127
1128 out ->Table16[i] = _cmsQuickSaturateWord(a* y + b);
1129 }
1130
1131
1132 return out;
1133 }
1134
1135 // Reverse a gamma table
1136 cmsToneCurve* CMSEXPORT cmsReverseToneCurve(cmsContext ContextID, const cmsToneCurve* InGamma)
1137 {
1138 _cmsAssert(InGamma != NULL);
1139
1140 return cmsReverseToneCurveEx(ContextID, 4096, InGamma);
1141 }
1142
1143 // From: Eilers, P.H.C. (1994) Smoothing and interpolation with finite
1144 // differences. in: Graphic Gems IV, Heckbert, P.S. (ed.), Academic press.
1145 //
1146 // Smoothing and interpolation with second differences.
1147 //
1148 // Input: weights (w), data (y): vector from 1 to m.
1149 // Input: smoothing parameter (lambda), length (m).
1150 // Output: smoothed vector (z): vector from 1 to m.
1151
1152 static
1153 cmsBool smooth2(cmsContext ContextID, cmsFloat32Number w[], cmsFloat32Number y[],
1154 cmsFloat32Number z[], cmsFloat32Number lambda, int m)
1155 {
1156 int i, i1, i2;
1157 cmsFloat32Number *c, *d, *e;
1158 cmsBool st;
1159
1160
1161 c = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number));
1162 d = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number));
1163 e = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number));
1164
1165 if (c != NULL && d != NULL && e != NULL) {
1166
1167
1168 d[1] = w[1] + lambda;
1169 c[1] = -2 * lambda / d[1];
1170 e[1] = lambda /d[1];
1171 z[1] = w[1] * y[1];
1172 d[2] = w[2] + 5 * lambda - d[1] * c[1] * c[1];
1173 c[2] = (-4 * lambda - d[1] * c[1] * e[1]) / d[2];
1174 e[2] = lambda / d[2];
1175 z[2] = w[2] * y[2] - c[1] * z[1];
1176
1177 for (i = 3; i < m - 1; i++) {
1178 i1 = i - 1; i2 = i - 2;
1179 d[i]= w[i] + 6 * lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2];
1180 c[i] = (-4 * lambda -d[i1] * c[i1] * e[i1])/ d[i];
1181 e[i] = lambda / d[i];
1182 z[i] = w[i] * y[i] - c[i1] * z[i1] - e[i2] * z[i2];
1183 }
1184
1185 i1 = m - 2; i2 = m - 3;
1186
1187 d[m - 1] = w[m - 1] + 5 * lambda -c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2];
1188 c[m - 1] = (-2 * lambda - d[i1] * c[i1] * e[i1]) / d[m - 1];
1189 z[m - 1] = w[m - 1] * y[m - 1] - c[i1] * z[i1] - e[i2] * z[i2];
1190 i1 = m - 1; i2 = m - 2;
1191
1192 d[m] = w[m] + lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2];
1193 z[m] = (w[m] * y[m] - c[i1] * z[i1] - e[i2] * z[i2]) / d[m];
1194 z[m - 1] = z[m - 1] / d[m - 1] - c[m - 1] * z[m];
1195
1196 for (i = m - 2; 1<= i; i--)
1197 z[i] = z[i] / d[i] - c[i] * z[i + 1] - e[i] * z[i + 2];
1198
1199 st = TRUE;
1200 }
1201 else st = FALSE;
1202
1203 if (c != NULL) _cmsFree(ContextID, c);
1204 if (d != NULL) _cmsFree(ContextID, d);
1205 if (e != NULL) _cmsFree(ContextID, e);
1206
1207 return st;
1208 }
1209
1210 // Smooths a curve sampled at regular intervals.
1211 cmsBool CMSEXPORT cmsSmoothToneCurve(cmsContext ContextID, cmsToneCurve* Tab, cmsFloat64Number lambda)
1212 {
1213 cmsBool SuccessStatus = TRUE;
1214 cmsFloat32Number *w, *y, *z;
1215 cmsUInt32Number i, nItems, Zeros, Poles;
1216 cmsBool notCheck = FALSE;
1217
1218 if (Tab != NULL && Tab->InterpParams != NULL)
1219 {
1220 if (!cmsIsToneCurveLinear(ContextID, Tab)) // Only non-linear curves need smoothing
1221 {
1222 nItems = Tab->nEntries;
1223 if (nItems < MAX_NODES_IN_CURVE)
1224 {
1225 // Allocate one more item than needed
1226 w = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number));
1227 y = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number));
1228 z = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number));
1229
1230 if (w != NULL && y != NULL && z != NULL) // Ensure no memory allocation failure
1231 {
1232 memset(w, 0, (nItems + 1) * sizeof(cmsFloat32Number));
1233 memset(y, 0, (nItems + 1) * sizeof(cmsFloat32Number));
1234 memset(z, 0, (nItems + 1) * sizeof(cmsFloat32Number));
1235
1236 for (i = 0; i < nItems; i++)
1237 {
1238 y[i + 1] = (cmsFloat32Number)Tab->Table16[i];
1239 w[i + 1] = 1.0;
1240 }
1241
1242 if (lambda < 0)
1243 {
1244 notCheck = TRUE;
1245 lambda = -lambda;
1246 }
1247
1248 if (smooth2(ContextID, w, y, z, (cmsFloat32Number)lambda, (int)nItems))
1249 {
1250 // Do some reality - checking...
1251
1252 Zeros = Poles = 0;
1253 for (i = nItems; i > 1; --i)
1254 {
1255 if (z[i] == 0.) Zeros++;
1256 if (z[i] >= 65535.) Poles++;
1257 if (z[i] < z[i - 1])
1258 {
1259 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Non-Monotonic.");
1260 SuccessStatus = notCheck;
1261 break;
1262 }
1263 }
1264
1265 if (SuccessStatus && Zeros > (nItems / 3))
1266 {
1267 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly zeros.");
1268 SuccessStatus = notCheck;
1269 }
1270
1271 if (SuccessStatus && Poles > (nItems / 3))
1272 {
1273 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly poles.");
1274 SuccessStatus = notCheck;
1275 }
1276
1277 if (SuccessStatus) // Seems ok
1278 {
1279 for (i = 0; i < nItems; i++)
1280 {
1281 // Clamp to cmsUInt16Number
1282 Tab->Table16[i] = _cmsQuickSaturateWord(z[i + 1]);
1283 }
1284 }
1285 }
1286 else // Could not smooth
1287 {
1288 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Function smooth2 failed.");
1289 SuccessStatus = FALSE;
1290 }
1291 }
1292 else // One or more buffers could not be allocated
1293 {
1294 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Could not allocate memory.");
1295 SuccessStatus = FALSE;
1296 }
1297
1298 if (z != NULL)
1299 _cmsFree(ContextID, z);
1300
1301 if (y != NULL)
1302 _cmsFree(ContextID, y);
1303
1304 if (w != NULL)
1305 _cmsFree(ContextID, w);
1306 }
1307 else // too many items in the table
1308 {
1309 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Too many points.");
1310 SuccessStatus = FALSE;
1311 }
1312 }
1313 }
1314 else // Tab parameter or Tab->InterpParams is NULL
1315 {
1316 // Can't signal an error here since the ContextID is not known at this point
1317 SuccessStatus = FALSE;
1318 }
1319
1320 return SuccessStatus;
1321 }
1322
1323 // Is a table linear? Do not use parametric since we cannot guarantee some weird parameters resulting
1324 // in a linear table. This way assures it is linear in 12 bits, which should be enough in most cases.
1325 cmsBool CMSEXPORT cmsIsToneCurveLinear(cmsContext ContextID, const cmsToneCurve* Curve)
1326 {
1327 int i;
1328 int diff;
1329 cmsUNUSED_PARAMETER(ContextID);
1330
1331 _cmsAssert(Curve != NULL);
1332
1333 for (i=0; i < (int) Curve ->nEntries; i++) {
1334
1335 diff = abs((int) Curve->Table16[i] - (int) _cmsQuantizeVal(i, Curve ->nEntries));
1336 if (diff > 0x0f)
1337 return FALSE;
1338 }
1339
1340 return TRUE;
1341 }
1342
1343 // Same, but for monotonicity
1344 cmsBool CMSEXPORT cmsIsToneCurveMonotonic(cmsContext ContextID, const cmsToneCurve* t)
1345 {
1346 cmsUInt32Number n;
1347 int i, last;
1348 cmsBool lDescending;
1349
1350 _cmsAssert(t != NULL);
1351
1352 // Degenerated curves are monotonic? Ok, let's pass them
1353 n = t ->nEntries;
1354 if (n < 2) return TRUE;
1355
1356 // Curve direction
1357 lDescending = cmsIsToneCurveDescending(ContextID, t);
1358
1359 if (lDescending) {
1360
1361 last = t ->Table16[0];
1362
1363 for (i = 1; i < (int) n; i++) {
1364
1365 if (t ->Table16[i] - last > 2) // We allow some ripple
1366 return FALSE;
1367 else
1368 last = t ->Table16[i];
1369
1370 }
1371 }
1372 else {
1373
1374 last = t ->Table16[n-1];
1375
1376 for (i = (int) n - 2; i >= 0; --i) {
1377
1378 if (t ->Table16[i] - last > 2)
1379 return FALSE;
1380 else
1381 last = t ->Table16[i];
1382
1383 }
1384 }
1385
1386 return TRUE;
1387 }
1388
1389 // Same, but for descending tables
1390 cmsBool CMSEXPORT cmsIsToneCurveDescending(cmsContext ContextID, const cmsToneCurve* t)
1391 {
1392 _cmsAssert(t != NULL);
1393 cmsUNUSED_PARAMETER(ContextID);
1394
1395 return t ->Table16[0] > t ->Table16[t ->nEntries-1];
1396 }
1397
1398
1399 // Another info fn: is out gamma table multisegment?
1400 cmsBool CMSEXPORT cmsIsToneCurveMultisegment(cmsContext ContextID, const cmsToneCurve* t)
1401 {
1402 _cmsAssert(t != NULL);
1403 cmsUNUSED_PARAMETER(ContextID);
1404
1405 return t -> nSegments > 1;
1406 }
1407
1408 cmsInt32Number CMSEXPORT cmsGetToneCurveParametricType(cmsContext ContextID, const cmsToneCurve* t)
1409 {
1410 _cmsAssert(t != NULL);
1411 cmsUNUSED_PARAMETER(ContextID);
1412
1413 if (t -> nSegments != 1) return 0;
1414 return t ->Segments[0].Type;
1415 }
1416
1417 // We need accuracy this time
1418 cmsFloat32Number CMSEXPORT cmsEvalToneCurveFloat(cmsContext ContextID, const cmsToneCurve* Curve, cmsFloat32Number v)
1419 {
1420 _cmsAssert(Curve != NULL);
1421
1422 // Check for 16 bits table. If so, this is a limited-precision tone curve
1423 if (Curve ->nSegments == 0) {
1424
1425 cmsUInt16Number In, Out;
1426
1427 In = (cmsUInt16Number) _cmsQuickSaturateWord(v * 65535.0);
1428 Out = cmsEvalToneCurve16(ContextID, Curve, In);
1429
1430 return (cmsFloat32Number) (Out / 65535.0);
1431 }
1432
1433 return (cmsFloat32Number) EvalSegmentedFn(ContextID, Curve, v);
1434 }
1435
1436 // We need xput over here
1437 cmsUInt16Number CMSEXPORT cmsEvalToneCurve16(cmsContext ContextID, const cmsToneCurve* Curve, cmsUInt16Number v)
1438 {
1439 cmsUInt16Number out;
1440
1441 _cmsAssert(Curve != NULL);
1442
1443 Curve ->InterpParams ->Interpolation.Lerp16(ContextID, &v, &out, Curve ->InterpParams);
1444 return out;
1445 }
1446
1447
1448 // Least squares fitting.
1449 // A mathematical procedure for finding the best-fitting curve to a given set of points by
1450 // minimizing the sum of the squares of the offsets ("the residuals") of the points from the curve.
1451 // The sum of the squares of the offsets is used instead of the offset absolute values because
1452 // this allows the residuals to be treated as a continuous differentiable quantity.
1453 //
1454 // y = f(x) = x ^ g
1455 //
1456 // R = (yi - (xi^g))
1457 // R2 = (yi - (xi^g))2
1458 // SUM R2 = SUM (yi - (xi^g))2
1459 //
1460 // dR2/dg = -2 SUM x^g log(x)(y - x^g)
1461 // solving for dR2/dg = 0
1462 //
1463 // g = 1/n * SUM(log(y) / log(x))
1464
1465 cmsFloat64Number CMSEXPORT cmsEstimateGamma(cmsContext ContextID, const cmsToneCurve* t, cmsFloat64Number Precision)
1466 {
1467 cmsFloat64Number gamma, sum, sum2;
1468 cmsFloat64Number n, x, y, Std;
1469 cmsUInt32Number i;
1470
1471 _cmsAssert(t != NULL);
1472
1473 sum = sum2 = n = 0;
1474
1475 // Excluding endpoints
1476 for (i=1; i < (MAX_NODES_IN_CURVE-1); i++) {
1477
1478 x = (cmsFloat64Number) i / (MAX_NODES_IN_CURVE-1);
1479 y = (cmsFloat64Number) cmsEvalToneCurveFloat(ContextID, t, (cmsFloat32Number) x);
1480
1481 // Avoid 7% on lower part to prevent
1482 // artifacts due to linear ramps
1483
1484 if (y > 0. && y < 1. && x > 0.07) {
1485
1486 gamma = log(y) / log(x);
1487 sum += gamma;
1488 sum2 += gamma * gamma;
1489 n++;
1490 }
1491 }
1492
1493 // We need enough valid samples
1494 if (n <= 1) return -1.0;
1495
1496 // Take a look on SD to see if gamma isn't exponential at all
1497 Std = sqrt((n * sum2 - sum * sum) / (n*(n-1)));
1498
1499 if (Std > Precision)
1500 return -1.0;
1501
1502 return (sum / n); // The mean
1503 }
1504
1505 // Retrieve segments on tone curves
1506
1507 const cmsCurveSegment* CMSEXPORT cmsGetToneCurveSegment(cmsContext contextID, cmsInt32Number n, const cmsToneCurve* t)
1508 {
1509 _cmsAssert(t != NULL);
1510
1511 if (n < 0 || n >= (cmsInt32Number) t->nSegments) return NULL;
1512 return t->Segments + n;
1513 }
1514