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(cmsInt32Number Type, const cmsFloat64Number Params[], cmsFloat64Number R);
59
60 // The built-in list
61 static const _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
DupPluginCurvesList(struct _cmsContext_struct * ctx,const struct _cmsContext_struct * src)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
_cmsAllocCurvesPluginChunk(struct _cmsContext_struct * ctx,const struct _cmsContext_struct * src)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
_cmsRegisterParametricCurvesPlugin(cmsContext ContextID,cmsPluginBase * Data)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
IsInSet(int Type,const _cmsParametricCurvesCollection * c)165 int IsInSet(int Type, const _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
GetParametricCurveByType(cmsContext ContextID,int Type,int * index)178 const _cmsParametricCurvesCollection *GetParametricCurveByType(cmsContext ContextID, int Type, int* index)
179 {
180 const _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
AllocateToneCurveStruct(cmsContext ContextID,cmsUInt32Number nEntries,cmsUInt32Number nSegments,const cmsCurveSegment * Segments,const cmsUInt16Number * Values)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 const _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 if (p -> SegInterp) _cmsFree(ContextID, p -> SegInterp);
304 if (p -> Segments) _cmsFree(ContextID, p -> Segments);
305 if (p -> Evals) _cmsFree(ContextID, p -> Evals);
306 if (p ->Table16) _cmsFree(ContextID, p ->Table16);
307 _cmsFree(ContextID, p);
308 return NULL;
309 }
310
311
312 // Generates a sigmoidal function with desired steepness.
sigmoid_base(double k,double t)313 cmsINLINE double sigmoid_base(double k, double t)
314 {
315 return (1.0 / (1.0 + exp(-k * t))) - 0.5;
316 }
317
inverted_sigmoid_base(double k,double t)318 cmsINLINE double inverted_sigmoid_base(double k, double t)
319 {
320 return -log((1.0 / (t + 0.5)) - 1.0) / k;
321 }
322
sigmoid_factory(double k,double t)323 cmsINLINE double sigmoid_factory(double k, double t)
324 {
325 double correction = 0.5 / sigmoid_base(k, 1);
326
327 return correction * sigmoid_base(k, 2.0 * t - 1.0) + 0.5;
328 }
329
inverse_sigmoid_factory(double k,double t)330 cmsINLINE double inverse_sigmoid_factory(double k, double t)
331 {
332 double correction = 0.5 / sigmoid_base(k, 1);
333
334 return (inverted_sigmoid_base(k, (t - 0.5) / correction) + 1.0) / 2.0;
335 }
336
337
338 // Parametric Fn using floating point
339 static
DefaultEvalParametricFn(cmsInt32Number Type,const cmsFloat64Number Params[],cmsFloat64Number R)340 cmsFloat64Number DefaultEvalParametricFn(cmsInt32Number Type, const cmsFloat64Number Params[], cmsFloat64Number R)
341 {
342 cmsFloat64Number e, Val, disc;
343
344 switch (Type) {
345
346 // X = Y ^ Gamma
347 case 1:
348 if (R < 0) {
349
350 if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE)
351 Val = R;
352 else
353 Val = 0;
354 }
355 else
356 Val = pow(R, Params[0]);
357 break;
358
359 // Type 1 Reversed: X = Y ^1/gamma
360 case -1:
361 if (R < 0) {
362
363 if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE)
364 Val = R;
365 else
366 Val = 0;
367 }
368 else
369 {
370 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE)
371 Val = PLUS_INF;
372 else
373 Val = pow(R, 1 / Params[0]);
374 }
375 break;
376
377 // CIE 122-1966
378 // Y = (aX + b)^Gamma | X >= -b/a
379 // Y = 0 | else
380 case 2:
381 {
382
383 if (fabs(Params[1]) < MATRIX_DET_TOLERANCE)
384 {
385 Val = 0;
386 }
387 else
388 {
389 disc = -Params[2] / Params[1];
390
391 if (R >= disc) {
392
393 e = Params[1] * R + Params[2];
394
395 if (e > 0)
396 Val = pow(e, Params[0]);
397 else
398 Val = 0;
399 }
400 else
401 Val = 0;
402 }
403 }
404 break;
405
406 // Type 2 Reversed
407 // X = (Y ^1/g - b) / a
408 case -2:
409 {
410 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
411 fabs(Params[1]) < MATRIX_DET_TOLERANCE)
412 {
413 Val = 0;
414 }
415 else
416 {
417 if (R < 0)
418 Val = 0;
419 else
420 Val = (pow(R, 1.0 / Params[0]) - Params[2]) / Params[1];
421
422 if (Val < 0)
423 Val = 0;
424 }
425 }
426 break;
427
428
429 // IEC 61966-3
430 // Y = (aX + b)^Gamma + c | X <= -b/a
431 // Y = c | else
432 case 3:
433 {
434 if (fabs(Params[1]) < MATRIX_DET_TOLERANCE)
435 {
436 Val = 0;
437 }
438 else
439 {
440 disc = -Params[2] / Params[1];
441 if (disc < 0)
442 disc = 0;
443
444 if (R >= disc) {
445
446 e = Params[1] * R + Params[2];
447
448 if (e > 0)
449 Val = pow(e, Params[0]) + Params[3];
450 else
451 Val = 0;
452 }
453 else
454 Val = Params[3];
455 }
456 }
457 break;
458
459
460 // Type 3 reversed
461 // X=((Y-c)^1/g - b)/a | (Y>=c)
462 // X=-b/a | (Y<c)
463 case -3:
464 {
465 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
466 fabs(Params[1]) < MATRIX_DET_TOLERANCE)
467 {
468 Val = 0;
469 }
470 else
471 {
472 if (R >= Params[3]) {
473
474 e = R - Params[3];
475
476 if (e > 0)
477 Val = (pow(e, 1 / Params[0]) - Params[2]) / Params[1];
478 else
479 Val = 0;
480 }
481 else {
482 Val = -Params[2] / Params[1];
483 }
484 }
485 }
486 break;
487
488
489 // IEC 61966-2.1 (sRGB)
490 // Y = (aX + b)^Gamma | X >= d
491 // Y = cX | X < d
492 case 4:
493 if (R >= Params[4]) {
494
495 e = Params[1]*R + Params[2];
496
497 if (e > 0)
498 Val = pow(e, Params[0]);
499 else
500 Val = 0;
501 }
502 else
503 Val = R * Params[3];
504 break;
505
506 // Type 4 reversed
507 // X=((Y^1/g-b)/a) | Y >= (ad+b)^g
508 // X=Y/c | Y< (ad+b)^g
509 case -4:
510 {
511
512 e = Params[1] * Params[4] + Params[2];
513 if (e < 0)
514 disc = 0;
515 else
516 disc = pow(e, Params[0]);
517
518 if (R >= disc) {
519
520 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
521 fabs(Params[1]) < MATRIX_DET_TOLERANCE)
522
523 Val = 0;
524
525 else
526 Val = (pow(R, 1.0 / Params[0]) - Params[2]) / Params[1];
527 }
528 else {
529
530 if (fabs(Params[3]) < MATRIX_DET_TOLERANCE)
531 Val = 0;
532 else
533 Val = R / Params[3];
534 }
535
536 }
537 break;
538
539
540 // Y = (aX + b)^Gamma + e | X >= d
541 // Y = cX + f | X < d
542 case 5:
543 if (R >= Params[4]) {
544
545 e = Params[1]*R + Params[2];
546
547 if (e > 0)
548 Val = pow(e, Params[0]) + Params[5];
549 else
550 Val = Params[5];
551 }
552 else
553 Val = R*Params[3] + Params[6];
554 break;
555
556
557 // Reversed type 5
558 // X=((Y-e)1/g-b)/a | Y >=(ad+b)^g+e), cd+f
559 // X=(Y-f)/c | else
560 case -5:
561 {
562 disc = Params[3] * Params[4] + Params[6];
563 if (R >= disc) {
564
565 e = R - Params[5];
566 if (e < 0)
567 Val = 0;
568 else
569 {
570 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
571 fabs(Params[1]) < MATRIX_DET_TOLERANCE)
572
573 Val = 0;
574 else
575 Val = (pow(e, 1.0 / Params[0]) - Params[2]) / Params[1];
576 }
577 }
578 else {
579 if (fabs(Params[3]) < MATRIX_DET_TOLERANCE)
580 Val = 0;
581 else
582 Val = (R - Params[6]) / Params[3];
583 }
584
585 }
586 break;
587
588
589 // Types 6,7,8 comes from segmented curves as described in ICCSpecRevision_02_11_06_Float.pdf
590 // Type 6 is basically identical to type 5 without d
591
592 // Y = (a * X + b) ^ Gamma + c
593 case 6:
594 e = Params[1]*R + Params[2];
595
596 if (e < 0)
597 Val = Params[3];
598 else
599 Val = pow(e, Params[0]) + Params[3];
600 break;
601
602 // ((Y - c) ^1/Gamma - b) / a
603 case -6:
604 {
605 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
606 fabs(Params[1]) < MATRIX_DET_TOLERANCE)
607 {
608 Val = 0;
609 }
610 else
611 {
612 e = R - Params[3];
613 if (e < 0)
614 Val = 0;
615 else
616 Val = (pow(e, 1.0 / Params[0]) - Params[2]) / Params[1];
617 }
618 }
619 break;
620
621
622 // Y = a * log (b * X^Gamma + c) + d
623 case 7:
624
625 e = Params[2] * pow(R, Params[0]) + Params[3];
626 if (e <= 0)
627 Val = Params[4];
628 else
629 Val = Params[1]*log10(e) + Params[4];
630 break;
631
632 // (Y - d) / a = log(b * X ^Gamma + c)
633 // pow(10, (Y-d) / a) = b * X ^Gamma + c
634 // pow((pow(10, (Y-d) / a) - c) / b, 1/g) = X
635 case -7:
636 {
637 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
638 fabs(Params[1]) < MATRIX_DET_TOLERANCE ||
639 fabs(Params[2]) < MATRIX_DET_TOLERANCE)
640 {
641 Val = 0;
642 }
643 else
644 {
645 Val = pow((pow(10.0, (R - Params[4]) / Params[1]) - Params[3]) / Params[2], 1.0 / Params[0]);
646 }
647 }
648 break;
649
650
651 //Y = a * b^(c*X+d) + e
652 case 8:
653 Val = (Params[0] * pow(Params[1], Params[2] * R + Params[3]) + Params[4]);
654 break;
655
656
657 // Y = (log((y-e) / a) / log(b) - d ) / c
658 // a=0, b=1, c=2, d=3, e=4,
659 case -8:
660
661 disc = R - Params[4];
662 if (disc < 0) Val = 0;
663 else
664 {
665 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
666 fabs(Params[2]) < MATRIX_DET_TOLERANCE)
667 {
668 Val = 0;
669 }
670 else
671 {
672 Val = (log(disc / Params[0]) / log(Params[1]) - Params[3]) / Params[2];
673 }
674 }
675 break;
676
677
678 // S-Shaped: (1 - (1-x)^1/g)^1/g
679 case 108:
680 if (fabs(Params[0]) < MATRIX_DET_TOLERANCE)
681 Val = 0;
682 else
683 Val = pow(1.0 - pow(1 - R, 1/Params[0]), 1/Params[0]);
684 break;
685
686 // y = (1 - (1-x)^1/g)^1/g
687 // y^g = (1 - (1-x)^1/g)
688 // 1 - y^g = (1-x)^1/g
689 // (1 - y^g)^g = 1 - x
690 // 1 - (1 - y^g)^g
691 case -108:
692 Val = 1 - pow(1 - pow(R, Params[0]), Params[0]);
693 break;
694
695 // Sigmoidals
696 case 109:
697 Val = sigmoid_factory(Params[0], R);
698 break;
699
700 case -109:
701 Val = inverse_sigmoid_factory(Params[0], R);
702 break;
703
704 default:
705 // Unsupported parametric curve. Should never reach here
706 return 0;
707 }
708
709 return Val;
710 }
711
712 // Evaluate a segmented function for a single value. Return -Inf if no valid segment found .
713 // If fn type is 0, perform an interpolation on the table
714 static
EvalSegmentedFn(const cmsToneCurve * g,cmsFloat64Number R)715 cmsFloat64Number EvalSegmentedFn(const cmsToneCurve *g, cmsFloat64Number R)
716 {
717 int i;
718 cmsFloat32Number Out32;
719 cmsFloat64Number Out;
720
721 for (i = (int) g->nSegments - 1; i >= 0; --i) {
722
723 // Check for domain
724 if ((R > g->Segments[i].x0) && (R <= g->Segments[i].x1)) {
725
726 // Type == 0 means segment is sampled
727 if (g->Segments[i].Type == 0) {
728
729 cmsFloat32Number R1 = (cmsFloat32Number)(R - g->Segments[i].x0) / (g->Segments[i].x1 - g->Segments[i].x0);
730
731 // Setup the table (TODO: clean that)
732 g->SegInterp[i]->Table = g->Segments[i].SampledPoints;
733
734 g->SegInterp[i]->Interpolation.LerpFloat(&R1, &Out32, g->SegInterp[i]);
735 Out = (cmsFloat64Number) Out32;
736
737 }
738 else {
739 Out = g->Evals[i](g->Segments[i].Type, g->Segments[i].Params, R);
740 }
741
742 if (isinf(Out))
743 return PLUS_INF;
744 else
745 {
746 if (isinf(-Out))
747 return MINUS_INF;
748 }
749
750 return Out;
751 }
752 }
753
754 return MINUS_INF;
755 }
756
757 // Access to estimated low-res table
cmsGetToneCurveEstimatedTableEntries(const cmsToneCurve * t)758 cmsUInt32Number CMSEXPORT cmsGetToneCurveEstimatedTableEntries(const cmsToneCurve* t)
759 {
760 _cmsAssert(t != NULL);
761 return t ->nEntries;
762 }
763
cmsGetToneCurveEstimatedTable(const cmsToneCurve * t)764 const cmsUInt16Number* CMSEXPORT cmsGetToneCurveEstimatedTable(const cmsToneCurve* t)
765 {
766 _cmsAssert(t != NULL);
767 return t ->Table16;
768 }
769
770
771 // Create an empty gamma curve, by using tables. This specifies only the limited-precision part, and leaves the
772 // floating point description empty.
cmsBuildTabulatedToneCurve16(cmsContext ContextID,cmsUInt32Number nEntries,const cmsUInt16Number Values[])773 cmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurve16(cmsContext ContextID, cmsUInt32Number nEntries, const cmsUInt16Number Values[])
774 {
775 return AllocateToneCurveStruct(ContextID, nEntries, 0, NULL, Values);
776 }
777
778 static
EntriesByGamma(cmsFloat64Number Gamma)779 cmsUInt32Number EntriesByGamma(cmsFloat64Number Gamma)
780 {
781 if (fabs(Gamma - 1.0) < 0.001) return 2;
782 return 4096;
783 }
784
785
786 // Create a segmented gamma, fill the table
cmsBuildSegmentedToneCurve(cmsContext ContextID,cmsUInt32Number nSegments,const cmsCurveSegment Segments[])787 cmsToneCurve* CMSEXPORT cmsBuildSegmentedToneCurve(cmsContext ContextID,
788 cmsUInt32Number nSegments, const cmsCurveSegment Segments[])
789 {
790 cmsUInt32Number i;
791 cmsFloat64Number R, Val;
792 cmsToneCurve* g;
793 cmsUInt32Number nGridPoints = 4096;
794
795 _cmsAssert(Segments != NULL);
796
797 // Optimizatin for identity curves.
798 if (nSegments == 1 && Segments[0].Type == 1) {
799
800 nGridPoints = EntriesByGamma(Segments[0].Params[0]);
801 }
802
803 g = AllocateToneCurveStruct(ContextID, nGridPoints, nSegments, Segments, NULL);
804 if (g == NULL) return NULL;
805
806 // Once we have the floating point version, we can approximate a 16 bit table of 4096 entries
807 // for performance reasons. This table would normally not be used except on 8/16 bits transforms.
808 for (i = 0; i < nGridPoints; i++) {
809
810 R = (cmsFloat64Number) i / (nGridPoints-1);
811
812 Val = EvalSegmentedFn(g, R);
813
814 // Round and saturate
815 g ->Table16[i] = _cmsQuickSaturateWord(Val * 65535.0);
816 }
817
818 return g;
819 }
820
821 // Use a segmented curve to store the floating point table
cmsBuildTabulatedToneCurveFloat(cmsContext ContextID,cmsUInt32Number nEntries,const cmsFloat32Number values[])822 cmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurveFloat(cmsContext ContextID, cmsUInt32Number nEntries, const cmsFloat32Number values[])
823 {
824 cmsCurveSegment Seg[3];
825
826 // Do some housekeeping
827 if (nEntries == 0 || values == NULL)
828 return NULL;
829
830 // A segmented tone curve should have function segments in the first and last positions
831 // Initialize segmented curve part up to 0 to constant value = samples[0]
832 Seg[0].x0 = MINUS_INF;
833 Seg[0].x1 = 0;
834 Seg[0].Type = 6;
835
836 Seg[0].Params[0] = 1;
837 Seg[0].Params[1] = 0;
838 Seg[0].Params[2] = 0;
839 Seg[0].Params[3] = values[0];
840 Seg[0].Params[4] = 0;
841
842 // From zero to 1
843 Seg[1].x0 = 0;
844 Seg[1].x1 = 1.0;
845 Seg[1].Type = 0;
846
847 Seg[1].nGridPoints = nEntries;
848 Seg[1].SampledPoints = (cmsFloat32Number*) values;
849
850 // Final segment is constant = lastsample
851 Seg[2].x0 = 1.0;
852 Seg[2].x1 = PLUS_INF;
853 Seg[2].Type = 6;
854
855 Seg[2].Params[0] = 1;
856 Seg[2].Params[1] = 0;
857 Seg[2].Params[2] = 0;
858 Seg[2].Params[3] = values[nEntries-1];
859 Seg[2].Params[4] = 0;
860
861
862 return cmsBuildSegmentedToneCurve(ContextID, 3, Seg);
863 }
864
865 // Parametric curves
866 //
867 // Parameters goes as: Curve, a, b, c, d, e, f
868 // Type is the ICC type +1
869 // if type is negative, then the curve is analytically inverted
cmsBuildParametricToneCurve(cmsContext ContextID,cmsInt32Number Type,const cmsFloat64Number Params[])870 cmsToneCurve* CMSEXPORT cmsBuildParametricToneCurve(cmsContext ContextID, cmsInt32Number Type, const cmsFloat64Number Params[])
871 {
872 cmsCurveSegment Seg0;
873 int Pos = 0;
874 cmsUInt32Number size;
875 const _cmsParametricCurvesCollection* c = GetParametricCurveByType(ContextID, Type, &Pos);
876
877 _cmsAssert(Params != NULL);
878
879 if (c == NULL) {
880 cmsSignalError(ContextID, cmsERROR_UNKNOWN_EXTENSION, "Invalid parametric curve type %d", Type);
881 return NULL;
882 }
883
884 memset(&Seg0, 0, sizeof(Seg0));
885
886 Seg0.x0 = MINUS_INF;
887 Seg0.x1 = PLUS_INF;
888 Seg0.Type = Type;
889
890 size = c->ParameterCount[Pos] * sizeof(cmsFloat64Number);
891 memmove(Seg0.Params, Params, size);
892
893 return cmsBuildSegmentedToneCurve(ContextID, 1, &Seg0);
894 }
895
896
897
898 // Build a gamma table based on gamma constant
cmsBuildGamma(cmsContext ContextID,cmsFloat64Number Gamma)899 cmsToneCurve* CMSEXPORT cmsBuildGamma(cmsContext ContextID, cmsFloat64Number Gamma)
900 {
901 return cmsBuildParametricToneCurve(ContextID, 1, &Gamma);
902 }
903
904
905 // Free all memory taken by the gamma curve
cmsFreeToneCurve(cmsToneCurve * Curve)906 void CMSEXPORT cmsFreeToneCurve(cmsToneCurve* Curve)
907 {
908 cmsContext ContextID;
909
910 // added by Xiaochuan Liu
911 // Curve->InterpParams may be null
912 if (Curve == NULL || Curve->InterpParams == NULL) return;
913
914 ContextID = Curve ->InterpParams->ContextID;
915
916 _cmsFreeInterpParams(Curve ->InterpParams);
917 Curve ->InterpParams = NULL;
918
919 if (Curve -> Table16) {
920 _cmsFree(ContextID, Curve ->Table16);
921 Curve ->Table16 = NULL;
922 }
923
924 if (Curve ->Segments) {
925
926 cmsUInt32Number i;
927
928 for (i=0; i < Curve ->nSegments; i++) {
929
930 if (Curve ->Segments[i].SampledPoints) {
931 _cmsFree(ContextID, Curve ->Segments[i].SampledPoints);
932 Curve ->Segments[i].SampledPoints = NULL;
933 }
934
935 if (Curve ->SegInterp[i] != 0) {
936 _cmsFreeInterpParams(Curve->SegInterp[i]);
937 Curve->SegInterp[i] = NULL;
938 }
939 }
940
941 _cmsFree(ContextID, Curve ->Segments);
942 Curve ->Segments = NULL;
943 _cmsFree(ContextID, Curve ->SegInterp);
944 Curve ->SegInterp = NULL;
945 }
946
947 if (Curve -> Evals) {
948 _cmsFree(ContextID, Curve -> Evals);
949 Curve -> Evals = NULL;
950 }
951
952 _cmsFree(ContextID, Curve);
953 }
954
955 // Utility function, free 3 gamma tables
cmsFreeToneCurveTriple(cmsToneCurve * Curve[3])956 void CMSEXPORT cmsFreeToneCurveTriple(cmsToneCurve* Curve[3])
957 {
958
959 _cmsAssert(Curve != NULL);
960
961 if (Curve[0] != NULL) cmsFreeToneCurve(Curve[0]);
962 if (Curve[1] != NULL) cmsFreeToneCurve(Curve[1]);
963 if (Curve[2] != NULL) cmsFreeToneCurve(Curve[2]);
964
965 Curve[0] = Curve[1] = Curve[2] = NULL;
966 }
967
968
969 // Duplicate a gamma table
cmsDupToneCurve(const cmsToneCurve * In)970 cmsToneCurve* CMSEXPORT cmsDupToneCurve(const cmsToneCurve* In)
971 {
972 if (In == NULL) return NULL;
973
974 return AllocateToneCurveStruct(In ->InterpParams ->ContextID, In ->nEntries, In ->nSegments, In ->Segments, In ->Table16);
975 }
976
977 // Joins two curves for X and Y. Curves should be monotonic.
978 // We want to get
979 //
980 // y = Y^-1(X(t))
981 //
cmsJoinToneCurve(cmsContext ContextID,const cmsToneCurve * X,const cmsToneCurve * Y,cmsUInt32Number nResultingPoints)982 cmsToneCurve* CMSEXPORT cmsJoinToneCurve(cmsContext ContextID,
983 const cmsToneCurve* X,
984 const cmsToneCurve* Y, cmsUInt32Number nResultingPoints)
985 {
986 cmsToneCurve* out = NULL;
987 cmsToneCurve* Yreversed = NULL;
988 cmsFloat32Number t, x;
989 cmsFloat32Number* Res = NULL;
990 cmsUInt32Number i;
991
992
993 _cmsAssert(X != NULL);
994 _cmsAssert(Y != NULL);
995
996 Yreversed = cmsReverseToneCurveEx(nResultingPoints, Y);
997 if (Yreversed == NULL) goto Error;
998
999 Res = (cmsFloat32Number*) _cmsCalloc(ContextID, nResultingPoints, sizeof(cmsFloat32Number));
1000 if (Res == NULL) goto Error;
1001
1002 //Iterate
1003 for (i=0; i < nResultingPoints; i++) {
1004
1005 t = (cmsFloat32Number) i / (cmsFloat32Number)(nResultingPoints-1);
1006 x = cmsEvalToneCurveFloat(X, t);
1007 Res[i] = cmsEvalToneCurveFloat(Yreversed, x);
1008 }
1009
1010 // Allocate space for output
1011 out = cmsBuildTabulatedToneCurveFloat(ContextID, nResultingPoints, Res);
1012
1013 Error:
1014
1015 if (Res != NULL) _cmsFree(ContextID, Res);
1016 if (Yreversed != NULL) cmsFreeToneCurve(Yreversed);
1017
1018 return out;
1019 }
1020
1021
1022
1023 // Get the surrounding nodes. This is tricky on non-monotonic tables
1024 static
GetInterval(cmsFloat64Number In,const cmsUInt16Number LutTable[],const struct _cms_interp_struc * p)1025 int GetInterval(cmsFloat64Number In, const cmsUInt16Number LutTable[], const struct _cms_interp_struc* p)
1026 {
1027 int i;
1028 int y0, y1;
1029
1030 // A 1 point table is not allowed
1031 if (p -> Domain[0] < 1) return -1;
1032
1033 // Let's see if ascending or descending.
1034 if (LutTable[0] < LutTable[p ->Domain[0]]) {
1035
1036 // Table is overall ascending
1037 for (i = (int) p->Domain[0] - 1; i >= 0; --i) {
1038
1039 y0 = LutTable[i];
1040 y1 = LutTable[i+1];
1041
1042 if (y0 <= y1) { // Increasing
1043 if (In >= y0 && In <= y1) return i;
1044 }
1045 else
1046 if (y1 < y0) { // Decreasing
1047 if (In >= y1 && In <= y0) return i;
1048 }
1049 }
1050 }
1051 else {
1052 // Table is overall descending
1053 for (i=0; i < (int) p -> Domain[0]; i++) {
1054
1055 y0 = LutTable[i];
1056 y1 = LutTable[i+1];
1057
1058 if (y0 <= y1) { // Increasing
1059 if (In >= y0 && In <= y1) return i;
1060 }
1061 else
1062 if (y1 < y0) { // Decreasing
1063 if (In >= y1 && In <= y0) return i;
1064 }
1065 }
1066 }
1067
1068 return -1;
1069 }
1070
1071 // Reverse a gamma table
cmsReverseToneCurveEx(cmsUInt32Number nResultSamples,const cmsToneCurve * InCurve)1072 cmsToneCurve* CMSEXPORT cmsReverseToneCurveEx(cmsUInt32Number nResultSamples, const cmsToneCurve* InCurve)
1073 {
1074 cmsToneCurve *out;
1075 cmsFloat64Number a = 0, b = 0, y, x1, y1, x2, y2;
1076 int i, j;
1077 int Ascending;
1078
1079 _cmsAssert(InCurve != NULL);
1080
1081 // Try to reverse it analytically whatever possible
1082
1083 if (InCurve ->nSegments == 1 && InCurve ->Segments[0].Type > 0 &&
1084 /* InCurve -> Segments[0].Type <= 5 */
1085 GetParametricCurveByType(InCurve ->InterpParams->ContextID, InCurve ->Segments[0].Type, NULL) != NULL) {
1086
1087 return cmsBuildParametricToneCurve(InCurve ->InterpParams->ContextID,
1088 -(InCurve -> Segments[0].Type),
1089 InCurve -> Segments[0].Params);
1090 }
1091
1092 // Nope, reverse the table.
1093 out = cmsBuildTabulatedToneCurve16(InCurve ->InterpParams->ContextID, nResultSamples, NULL);
1094 if (out == NULL)
1095 return NULL;
1096
1097 // We want to know if this is an ascending or descending table
1098 Ascending = !cmsIsToneCurveDescending(InCurve);
1099
1100 // Iterate across Y axis
1101 for (i=0; i < (int) nResultSamples; i++) {
1102
1103 y = (cmsFloat64Number) i * 65535.0 / (nResultSamples - 1);
1104
1105 // Find interval in which y is within.
1106 j = GetInterval(y, InCurve->Table16, InCurve->InterpParams);
1107 if (j >= 0) {
1108
1109
1110 // Get limits of interval
1111 x1 = InCurve ->Table16[j];
1112 x2 = InCurve ->Table16[j+1];
1113
1114 y1 = (cmsFloat64Number) (j * 65535.0) / (InCurve ->nEntries - 1);
1115 y2 = (cmsFloat64Number) ((j+1) * 65535.0 ) / (InCurve ->nEntries - 1);
1116
1117 // If collapsed, then use any
1118 if (x1 == x2) {
1119
1120 out ->Table16[i] = _cmsQuickSaturateWord(Ascending ? y2 : y1);
1121 continue;
1122
1123 } else {
1124
1125 // Interpolate
1126 a = (y2 - y1) / (x2 - x1);
1127 b = y2 - a * x2;
1128 }
1129 }
1130
1131 out ->Table16[i] = _cmsQuickSaturateWord(a* y + b);
1132 }
1133
1134
1135 return out;
1136 }
1137
1138 // Reverse a gamma table
cmsReverseToneCurve(const cmsToneCurve * InGamma)1139 cmsToneCurve* CMSEXPORT cmsReverseToneCurve(const cmsToneCurve* InGamma)
1140 {
1141 _cmsAssert(InGamma != NULL);
1142
1143 return cmsReverseToneCurveEx(4096, InGamma);
1144 }
1145
1146 // From: Eilers, P.H.C. (1994) Smoothing and interpolation with finite
1147 // differences. in: Graphic Gems IV, Heckbert, P.S. (ed.), Academic press.
1148 //
1149 // Smoothing and interpolation with second differences.
1150 //
1151 // Input: weights (w), data (y): vector from 1 to m.
1152 // Input: smoothing parameter (lambda), length (m).
1153 // Output: smoothed vector (z): vector from 1 to m.
1154
1155 static
smooth2(cmsContext ContextID,cmsFloat32Number w[],cmsFloat32Number y[],cmsFloat32Number z[],cmsFloat32Number lambda,int m)1156 cmsBool smooth2(cmsContext ContextID, cmsFloat32Number w[], cmsFloat32Number y[],
1157 cmsFloat32Number z[], cmsFloat32Number lambda, int m)
1158 {
1159 int i, i1, i2;
1160 cmsFloat32Number *c, *d, *e;
1161 cmsBool st;
1162
1163
1164 c = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number));
1165 d = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number));
1166 e = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number));
1167
1168 if (c != NULL && d != NULL && e != NULL) {
1169
1170
1171 d[1] = w[1] + lambda;
1172 c[1] = -2 * lambda / d[1];
1173 e[1] = lambda /d[1];
1174 z[1] = w[1] * y[1];
1175 d[2] = w[2] + 5 * lambda - d[1] * c[1] * c[1];
1176 c[2] = (-4 * lambda - d[1] * c[1] * e[1]) / d[2];
1177 e[2] = lambda / d[2];
1178 z[2] = w[2] * y[2] - c[1] * z[1];
1179
1180 for (i = 3; i < m - 1; i++) {
1181 i1 = i - 1; i2 = i - 2;
1182 d[i]= w[i] + 6 * lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2];
1183 c[i] = (-4 * lambda -d[i1] * c[i1] * e[i1])/ d[i];
1184 e[i] = lambda / d[i];
1185 z[i] = w[i] * y[i] - c[i1] * z[i1] - e[i2] * z[i2];
1186 }
1187
1188 i1 = m - 2; i2 = m - 3;
1189
1190 d[m - 1] = w[m - 1] + 5 * lambda -c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2];
1191 c[m - 1] = (-2 * lambda - d[i1] * c[i1] * e[i1]) / d[m - 1];
1192 z[m - 1] = w[m - 1] * y[m - 1] - c[i1] * z[i1] - e[i2] * z[i2];
1193 i1 = m - 1; i2 = m - 2;
1194
1195 d[m] = w[m] + lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2];
1196 z[m] = (w[m] * y[m] - c[i1] * z[i1] - e[i2] * z[i2]) / d[m];
1197 z[m - 1] = z[m - 1] / d[m - 1] - c[m - 1] * z[m];
1198
1199 for (i = m - 2; 1<= i; i--)
1200 z[i] = z[i] / d[i] - c[i] * z[i + 1] - e[i] * z[i + 2];
1201
1202 st = TRUE;
1203 }
1204 else st = FALSE;
1205
1206 if (c != NULL) _cmsFree(ContextID, c);
1207 if (d != NULL) _cmsFree(ContextID, d);
1208 if (e != NULL) _cmsFree(ContextID, e);
1209
1210 return st;
1211 }
1212
1213 // Smooths a curve sampled at regular intervals.
cmsSmoothToneCurve(cmsToneCurve * Tab,cmsFloat64Number lambda)1214 cmsBool CMSEXPORT cmsSmoothToneCurve(cmsToneCurve* Tab, cmsFloat64Number lambda)
1215 {
1216 cmsBool SuccessStatus = TRUE;
1217 cmsFloat32Number *w, *y, *z;
1218 cmsUInt32Number i, nItems, Zeros, Poles;
1219 cmsBool notCheck = FALSE;
1220
1221 if (Tab != NULL && Tab->InterpParams != NULL)
1222 {
1223 cmsContext ContextID = Tab->InterpParams->ContextID;
1224
1225 if (!cmsIsToneCurveLinear(Tab)) // Only non-linear curves need smoothing
1226 {
1227 nItems = Tab->nEntries;
1228 if (nItems < MAX_NODES_IN_CURVE)
1229 {
1230 // Allocate one more item than needed
1231 w = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number));
1232 y = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number));
1233 z = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number));
1234
1235 if (w != NULL && y != NULL && z != NULL) // Ensure no memory allocation failure
1236 {
1237 memset(w, 0, (nItems + 1) * sizeof(cmsFloat32Number));
1238 memset(y, 0, (nItems + 1) * sizeof(cmsFloat32Number));
1239 memset(z, 0, (nItems + 1) * sizeof(cmsFloat32Number));
1240
1241 for (i = 0; i < nItems; i++)
1242 {
1243 y[i + 1] = (cmsFloat32Number)Tab->Table16[i];
1244 w[i + 1] = 1.0;
1245 }
1246
1247 if (lambda < 0)
1248 {
1249 notCheck = TRUE;
1250 lambda = -lambda;
1251 }
1252
1253 if (smooth2(ContextID, w, y, z, (cmsFloat32Number)lambda, (int)nItems))
1254 {
1255 // Do some reality - checking...
1256
1257 Zeros = Poles = 0;
1258 for (i = nItems; i > 1; --i)
1259 {
1260 if (z[i] == 0.) Zeros++;
1261 if (z[i] >= 65535.) Poles++;
1262 if (z[i] < z[i - 1])
1263 {
1264 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Non-Monotonic.");
1265 SuccessStatus = notCheck;
1266 break;
1267 }
1268 }
1269
1270 if (SuccessStatus && Zeros > (nItems / 3))
1271 {
1272 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly zeros.");
1273 SuccessStatus = notCheck;
1274 }
1275
1276 if (SuccessStatus && Poles > (nItems / 3))
1277 {
1278 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly poles.");
1279 SuccessStatus = notCheck;
1280 }
1281
1282 if (SuccessStatus) // Seems ok
1283 {
1284 for (i = 0; i < nItems; i++)
1285 {
1286 // Clamp to cmsUInt16Number
1287 Tab->Table16[i] = _cmsQuickSaturateWord(z[i + 1]);
1288 }
1289 }
1290 }
1291 else // Could not smooth
1292 {
1293 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Function smooth2 failed.");
1294 SuccessStatus = FALSE;
1295 }
1296 }
1297 else // One or more buffers could not be allocated
1298 {
1299 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Could not allocate memory.");
1300 SuccessStatus = FALSE;
1301 }
1302
1303 if (z != NULL)
1304 _cmsFree(ContextID, z);
1305
1306 if (y != NULL)
1307 _cmsFree(ContextID, y);
1308
1309 if (w != NULL)
1310 _cmsFree(ContextID, w);
1311 }
1312 else // too many items in the table
1313 {
1314 cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Too many points.");
1315 SuccessStatus = FALSE;
1316 }
1317 }
1318 }
1319 else // Tab parameter or Tab->InterpParams is NULL
1320 {
1321 // Can't signal an error here since the ContextID is not known at this point
1322 SuccessStatus = FALSE;
1323 }
1324
1325 return SuccessStatus;
1326 }
1327
1328 // Is a table linear? Do not use parametric since we cannot guarantee some weird parameters resulting
1329 // in a linear table. This way assures it is linear in 12 bits, which should be enough in most cases.
cmsIsToneCurveLinear(const cmsToneCurve * Curve)1330 cmsBool CMSEXPORT cmsIsToneCurveLinear(const cmsToneCurve* Curve)
1331 {
1332 int i;
1333 int diff;
1334
1335 _cmsAssert(Curve != NULL);
1336
1337 for (i=0; i < (int) Curve ->nEntries; i++) {
1338
1339 diff = abs((int) Curve->Table16[i] - (int) _cmsQuantizeVal(i, Curve ->nEntries));
1340 if (diff > 0x0f)
1341 return FALSE;
1342 }
1343
1344 return TRUE;
1345 }
1346
1347 // Same, but for monotonicity
cmsIsToneCurveMonotonic(const cmsToneCurve * t)1348 cmsBool CMSEXPORT cmsIsToneCurveMonotonic(const cmsToneCurve* t)
1349 {
1350 cmsUInt32Number n;
1351 int i, last;
1352 cmsBool lDescending;
1353
1354 _cmsAssert(t != NULL);
1355
1356 // Degenerated curves are monotonic? Ok, let's pass them
1357 n = t ->nEntries;
1358 if (n < 2) return TRUE;
1359
1360 // Curve direction
1361 lDescending = cmsIsToneCurveDescending(t);
1362
1363 if (lDescending) {
1364
1365 last = t ->Table16[0];
1366
1367 for (i = 1; i < (int) n; i++) {
1368
1369 if (t ->Table16[i] - last > 2) // We allow some ripple
1370 return FALSE;
1371 else
1372 last = t ->Table16[i];
1373
1374 }
1375 }
1376 else {
1377
1378 last = t ->Table16[n-1];
1379
1380 for (i = (int) n - 2; i >= 0; --i) {
1381
1382 if (t ->Table16[i] - last > 2)
1383 return FALSE;
1384 else
1385 last = t ->Table16[i];
1386
1387 }
1388 }
1389
1390 return TRUE;
1391 }
1392
1393 // Same, but for descending tables
cmsIsToneCurveDescending(const cmsToneCurve * t)1394 cmsBool CMSEXPORT cmsIsToneCurveDescending(const cmsToneCurve* t)
1395 {
1396 _cmsAssert(t != NULL);
1397
1398 return t ->Table16[0] > t ->Table16[t ->nEntries-1];
1399 }
1400
1401
1402 // Another info fn: is out gamma table multisegment?
cmsIsToneCurveMultisegment(const cmsToneCurve * t)1403 cmsBool CMSEXPORT cmsIsToneCurveMultisegment(const cmsToneCurve* t)
1404 {
1405 _cmsAssert(t != NULL);
1406
1407 return t -> nSegments > 1;
1408 }
1409
cmsGetToneCurveParametricType(const cmsToneCurve * t)1410 cmsInt32Number CMSEXPORT cmsGetToneCurveParametricType(const cmsToneCurve* t)
1411 {
1412 _cmsAssert(t != NULL);
1413
1414 if (t -> nSegments != 1) return 0;
1415 return t ->Segments[0].Type;
1416 }
1417
1418 // We need accuracy this time
cmsEvalToneCurveFloat(const cmsToneCurve * Curve,cmsFloat32Number v)1419 cmsFloat32Number CMSEXPORT cmsEvalToneCurveFloat(const cmsToneCurve* Curve, cmsFloat32Number v)
1420 {
1421 _cmsAssert(Curve != NULL);
1422
1423 // Check for 16 bits table. If so, this is a limited-precision tone curve
1424 if (Curve ->nSegments == 0) {
1425
1426 cmsUInt16Number In, Out;
1427
1428 In = (cmsUInt16Number) _cmsQuickSaturateWord(v * 65535.0);
1429 Out = cmsEvalToneCurve16(Curve, In);
1430
1431 return (cmsFloat32Number) (Out / 65535.0);
1432 }
1433
1434 return (cmsFloat32Number) EvalSegmentedFn(Curve, v);
1435 }
1436
1437 // We need xput over here
cmsEvalToneCurve16(const cmsToneCurve * Curve,cmsUInt16Number v)1438 cmsUInt16Number CMSEXPORT cmsEvalToneCurve16(const cmsToneCurve* Curve, cmsUInt16Number v)
1439 {
1440 cmsUInt16Number out;
1441
1442 _cmsAssert(Curve != NULL);
1443
1444 Curve ->InterpParams ->Interpolation.Lerp16(&v, &out, Curve ->InterpParams);
1445 return out;
1446 }
1447
1448
1449 // Least squares fitting.
1450 // A mathematical procedure for finding the best-fitting curve to a given set of points by
1451 // minimizing the sum of the squares of the offsets ("the residuals") of the points from the curve.
1452 // The sum of the squares of the offsets is used instead of the offset absolute values because
1453 // this allows the residuals to be treated as a continuous differentiable quantity.
1454 //
1455 // y = f(x) = x ^ g
1456 //
1457 // R = (yi - (xi^g))
1458 // R2 = (yi - (xi^g))2
1459 // SUM R2 = SUM (yi - (xi^g))2
1460 //
1461 // dR2/dg = -2 SUM x^g log(x)(y - x^g)
1462 // solving for dR2/dg = 0
1463 //
1464 // g = 1/n * SUM(log(y) / log(x))
1465
cmsEstimateGamma(const cmsToneCurve * t,cmsFloat64Number Precision)1466 cmsFloat64Number CMSEXPORT cmsEstimateGamma(const cmsToneCurve* t, cmsFloat64Number Precision)
1467 {
1468 cmsFloat64Number gamma, sum, sum2;
1469 cmsFloat64Number n, x, y, Std;
1470 cmsUInt32Number i;
1471
1472 _cmsAssert(t != NULL);
1473
1474 sum = sum2 = n = 0;
1475
1476 // Excluding endpoints
1477 for (i=1; i < (MAX_NODES_IN_CURVE-1); i++) {
1478
1479 x = (cmsFloat64Number) i / (MAX_NODES_IN_CURVE-1);
1480 y = (cmsFloat64Number) cmsEvalToneCurveFloat(t, (cmsFloat32Number) x);
1481
1482 // Avoid 7% on lower part to prevent
1483 // artifacts due to linear ramps
1484
1485 if (y > 0. && y < 1. && x > 0.07) {
1486
1487 gamma = log(y) / log(x);
1488 sum += gamma;
1489 sum2 += gamma * gamma;
1490 n++;
1491 }
1492 }
1493
1494 // We need enough valid samples
1495 if (n <= 1) return -1.0;
1496
1497 // Take a look on SD to see if gamma isn't exponential at all
1498 Std = sqrt((n * sum2 - sum * sum) / (n*(n-1)));
1499
1500 if (Std > Precision)
1501 return -1.0;
1502
1503 return (sum / n); // The mean
1504 }
1505
1506
1507 // Retrieve parameters on one-segment tone curves
1508
cmsGetToneCurveParams(const cmsToneCurve * t)1509 cmsFloat64Number* CMSEXPORT cmsGetToneCurveParams(const cmsToneCurve* t)
1510 {
1511 _cmsAssert(t != NULL);
1512
1513 if (t->nSegments != 1) return NULL;
1514 return t->Segments[0].Params;
1515 }
1516