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PojavLauncherTeam
GitHub Repository: PojavLauncherTeam/openjdk-multiarch-jdk8u
Path: blob/aarch64-shenandoah-jdk8u272-b10/jdk/src/share/native/sun/java2d/cmm/lcms/cmsgamma.c
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/*
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* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
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*
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* This code is free software; you can redistribute it and/or modify it
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* under the terms of the GNU General Public License version 2 only, as
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* published by the Free Software Foundation. Oracle designates this
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* particular file as subject to the "Classpath" exception as provided
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* by Oracle in the LICENSE file that accompanied this code.
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*
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* This code is distributed in the hope that it will be useful, but WITHOUT
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* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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* version 2 for more details (a copy is included in the LICENSE file that
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* accompanied this code).
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*
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* You should have received a copy of the GNU General Public License version
17
* 2 along with this work; if not, write to the Free Software Foundation,
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* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
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*
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* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
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* or visit www.oracle.com if you need additional information or have any
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* questions.
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*/
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25
// This file is available under and governed by the GNU General Public
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// License version 2 only, as published by the Free Software Foundation.
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// However, the following notice accompanied the original version of this
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// file:
29
//
30
//---------------------------------------------------------------------------------
31
//
32
// Little Color Management System
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// Copyright (c) 1998-2020 Marti Maria Saguer
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//
35
// Permission is hereby granted, free of charge, to any person obtaining
36
// a copy of this software and associated documentation files (the "Software"),
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// to deal in the Software without restriction, including without limitation
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// the rights to use, copy, modify, merge, publish, distribute, sublicense,
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// and/or sell copies of the Software, and to permit persons to whom the Software
40
// is furnished to do so, subject to the following conditions:
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//
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// The above copyright notice and this permission notice shall be included in
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// all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
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// THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
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// LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
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// OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
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// WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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//
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//---------------------------------------------------------------------------------
54
//
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#include "lcms2_internal.h"
56
57
// Tone curves are powerful constructs that can contain curves specified in diverse ways.
58
// The curve is stored in segments, where each segment can be sampled or specified by parameters.
59
// a 16.bit simplification of the *whole* curve is kept for optimization purposes. For float operation,
60
// each segment is evaluated separately. Plug-ins may be used to define new parametric schemes,
61
// each plug-in may define up to MAX_TYPES_IN_LCMS_PLUGIN functions types. For defining a function,
62
// the plug-in should provide the type id, how many parameters each type has, and a pointer to
63
// a procedure that evaluates the function. In the case of reverse evaluation, the evaluator will
64
// be called with the type id as a negative value, and a sampled version of the reversed curve
65
// will be built.
66
67
// ----------------------------------------------------------------- Implementation
68
// Maxim number of nodes
69
#define MAX_NODES_IN_CURVE 4097
70
#define MINUS_INF (-1E22F)
71
#define PLUS_INF (+1E22F)
72
73
// The list of supported parametric curves
74
typedef struct _cmsParametricCurvesCollection_st {
75
76
cmsUInt32Number nFunctions; // Number of supported functions in this chunk
77
cmsInt32Number FunctionTypes[MAX_TYPES_IN_LCMS_PLUGIN]; // The identification types
78
cmsUInt32Number ParameterCount[MAX_TYPES_IN_LCMS_PLUGIN]; // Number of parameters for each function
79
80
cmsParametricCurveEvaluator Evaluator; // The evaluator
81
82
struct _cmsParametricCurvesCollection_st* Next; // Next in list
83
84
} _cmsParametricCurvesCollection;
85
86
// This is the default (built-in) evaluator
87
static cmsFloat64Number DefaultEvalParametricFn(cmsInt32Number Type, const cmsFloat64Number Params[], cmsFloat64Number R);
88
89
// The built-in list
90
static _cmsParametricCurvesCollection DefaultCurves = {
91
9, // # of curve types
92
{ 1, 2, 3, 4, 5, 6, 7, 8, 108 }, // Parametric curve ID
93
{ 1, 3, 4, 5, 7, 4, 5, 5, 1 }, // Parameters by type
94
DefaultEvalParametricFn, // Evaluator
95
NULL // Next in chain
96
};
97
98
// Duplicates the zone of memory used by the plug-in in the new context
99
static
100
void DupPluginCurvesList(struct _cmsContext_struct* ctx,
101
const struct _cmsContext_struct* src)
102
{
103
_cmsCurvesPluginChunkType newHead = { NULL };
104
_cmsParametricCurvesCollection* entry;
105
_cmsParametricCurvesCollection* Anterior = NULL;
106
_cmsCurvesPluginChunkType* head = (_cmsCurvesPluginChunkType*) src->chunks[CurvesPlugin];
107
108
_cmsAssert(head != NULL);
109
110
// Walk the list copying all nodes
111
for (entry = head->ParametricCurves;
112
entry != NULL;
113
entry = entry ->Next) {
114
115
_cmsParametricCurvesCollection *newEntry = ( _cmsParametricCurvesCollection *) _cmsSubAllocDup(ctx ->MemPool, entry, sizeof(_cmsParametricCurvesCollection));
116
117
if (newEntry == NULL)
118
return;
119
120
// We want to keep the linked list order, so this is a little bit tricky
121
newEntry -> Next = NULL;
122
if (Anterior)
123
Anterior -> Next = newEntry;
124
125
Anterior = newEntry;
126
127
if (newHead.ParametricCurves == NULL)
128
newHead.ParametricCurves = newEntry;
129
}
130
131
ctx ->chunks[CurvesPlugin] = _cmsSubAllocDup(ctx->MemPool, &newHead, sizeof(_cmsCurvesPluginChunkType));
132
}
133
134
// The allocator have to follow the chain
135
void _cmsAllocCurvesPluginChunk(struct _cmsContext_struct* ctx,
136
const struct _cmsContext_struct* src)
137
{
138
_cmsAssert(ctx != NULL);
139
140
if (src != NULL) {
141
142
// Copy all linked list
143
DupPluginCurvesList(ctx, src);
144
}
145
else {
146
static _cmsCurvesPluginChunkType CurvesPluginChunk = { NULL };
147
ctx ->chunks[CurvesPlugin] = _cmsSubAllocDup(ctx ->MemPool, &CurvesPluginChunk, sizeof(_cmsCurvesPluginChunkType));
148
}
149
}
150
151
152
// The linked list head
153
_cmsCurvesPluginChunkType _cmsCurvesPluginChunk = { NULL };
154
155
// As a way to install new parametric curves
156
cmsBool _cmsRegisterParametricCurvesPlugin(cmsContext ContextID, cmsPluginBase* Data)
157
{
158
_cmsCurvesPluginChunkType* ctx = ( _cmsCurvesPluginChunkType*) _cmsContextGetClientChunk(ContextID, CurvesPlugin);
159
cmsPluginParametricCurves* Plugin = (cmsPluginParametricCurves*) Data;
160
_cmsParametricCurvesCollection* fl;
161
162
if (Data == NULL) {
163
164
ctx -> ParametricCurves = NULL;
165
return TRUE;
166
}
167
168
fl = (_cmsParametricCurvesCollection*) _cmsPluginMalloc(ContextID, sizeof(_cmsParametricCurvesCollection));
169
if (fl == NULL) return FALSE;
170
171
// Copy the parameters
172
fl ->Evaluator = Plugin ->Evaluator;
173
fl ->nFunctions = Plugin ->nFunctions;
174
175
// Make sure no mem overwrites
176
if (fl ->nFunctions > MAX_TYPES_IN_LCMS_PLUGIN)
177
fl ->nFunctions = MAX_TYPES_IN_LCMS_PLUGIN;
178
179
// Copy the data
180
memmove(fl->FunctionTypes, Plugin ->FunctionTypes, fl->nFunctions * sizeof(cmsUInt32Number));
181
memmove(fl->ParameterCount, Plugin ->ParameterCount, fl->nFunctions * sizeof(cmsUInt32Number));
182
183
// Keep linked list
184
fl ->Next = ctx->ParametricCurves;
185
ctx->ParametricCurves = fl;
186
187
// All is ok
188
return TRUE;
189
}
190
191
192
// Search in type list, return position or -1 if not found
193
static
194
int IsInSet(int Type, _cmsParametricCurvesCollection* c)
195
{
196
int i;
197
198
for (i=0; i < (int) c ->nFunctions; i++)
199
if (abs(Type) == c ->FunctionTypes[i]) return i;
200
201
return -1;
202
}
203
204
205
// Search for the collection which contains a specific type
206
static
207
_cmsParametricCurvesCollection *GetParametricCurveByType(cmsContext ContextID, int Type, int* index)
208
{
209
_cmsParametricCurvesCollection* c;
210
int Position;
211
_cmsCurvesPluginChunkType* ctx = ( _cmsCurvesPluginChunkType*) _cmsContextGetClientChunk(ContextID, CurvesPlugin);
212
213
for (c = ctx->ParametricCurves; c != NULL; c = c ->Next) {
214
215
Position = IsInSet(Type, c);
216
217
if (Position != -1) {
218
if (index != NULL)
219
*index = Position;
220
return c;
221
}
222
}
223
// If none found, revert for defaults
224
for (c = &DefaultCurves; c != NULL; c = c ->Next) {
225
226
Position = IsInSet(Type, c);
227
228
if (Position != -1) {
229
if (index != NULL)
230
*index = Position;
231
return c;
232
}
233
}
234
235
return NULL;
236
}
237
238
// Low level allocate, which takes care of memory details. nEntries may be zero, and in this case
239
// no optimation curve is computed. nSegments may also be zero in the inverse case, where only the
240
// optimization curve is given. Both features simultaneously is an error
241
static
242
cmsToneCurve* AllocateToneCurveStruct(cmsContext ContextID, cmsUInt32Number nEntries,
243
cmsUInt32Number nSegments, const cmsCurveSegment* Segments,
244
const cmsUInt16Number* Values)
245
{
246
cmsToneCurve* p;
247
cmsUInt32Number i;
248
249
// We allow huge tables, which are then restricted for smoothing operations
250
if (nEntries > 65530) {
251
cmsSignalError(ContextID, cmsERROR_RANGE, "Couldn't create tone curve of more than 65530 entries");
252
return NULL;
253
}
254
255
if (nEntries == 0 && nSegments == 0) {
256
cmsSignalError(ContextID, cmsERROR_RANGE, "Couldn't create tone curve with zero segments and no table");
257
return NULL;
258
}
259
260
// Allocate all required pointers, etc.
261
p = (cmsToneCurve*) _cmsMallocZero(ContextID, sizeof(cmsToneCurve));
262
if (!p) return NULL;
263
264
// In this case, there are no segments
265
if (nSegments == 0) {
266
p ->Segments = NULL;
267
p ->Evals = NULL;
268
}
269
else {
270
p ->Segments = (cmsCurveSegment*) _cmsCalloc(ContextID, nSegments, sizeof(cmsCurveSegment));
271
if (p ->Segments == NULL) goto Error;
272
273
p ->Evals = (cmsParametricCurveEvaluator*) _cmsCalloc(ContextID, nSegments, sizeof(cmsParametricCurveEvaluator));
274
if (p ->Evals == NULL) goto Error;
275
}
276
277
p -> nSegments = nSegments;
278
279
// This 16-bit table contains a limited precision representation of the whole curve and is kept for
280
// increasing xput on certain operations.
281
if (nEntries == 0) {
282
p ->Table16 = NULL;
283
}
284
else {
285
p ->Table16 = (cmsUInt16Number*) _cmsCalloc(ContextID, nEntries, sizeof(cmsUInt16Number));
286
if (p ->Table16 == NULL) goto Error;
287
}
288
289
p -> nEntries = nEntries;
290
291
// Initialize members if requested
292
if (Values != NULL && (nEntries > 0)) {
293
294
for (i=0; i < nEntries; i++)
295
p ->Table16[i] = Values[i];
296
}
297
298
// Initialize the segments stuff. The evaluator for each segment is located and a pointer to it
299
// is placed in advance to maximize performance.
300
if (Segments != NULL && (nSegments > 0)) {
301
302
_cmsParametricCurvesCollection *c;
303
304
p ->SegInterp = (cmsInterpParams**) _cmsCalloc(ContextID, nSegments, sizeof(cmsInterpParams*));
305
if (p ->SegInterp == NULL) goto Error;
306
307
for (i=0; i < nSegments; i++) {
308
309
// Type 0 is a special marker for table-based curves
310
if (Segments[i].Type == 0)
311
p ->SegInterp[i] = _cmsComputeInterpParams(ContextID, Segments[i].nGridPoints, 1, 1, NULL, CMS_LERP_FLAGS_FLOAT);
312
313
memmove(&p ->Segments[i], &Segments[i], sizeof(cmsCurveSegment));
314
315
if (Segments[i].Type == 0 && Segments[i].SampledPoints != NULL)
316
p ->Segments[i].SampledPoints = (cmsFloat32Number*) _cmsDupMem(ContextID, Segments[i].SampledPoints, sizeof(cmsFloat32Number) * Segments[i].nGridPoints);
317
else
318
p ->Segments[i].SampledPoints = NULL;
319
320
321
c = GetParametricCurveByType(ContextID, Segments[i].Type, NULL);
322
if (c != NULL)
323
p ->Evals[i] = c ->Evaluator;
324
}
325
}
326
327
p ->InterpParams = _cmsComputeInterpParams(ContextID, p ->nEntries, 1, 1, p->Table16, CMS_LERP_FLAGS_16BITS);
328
if (p->InterpParams != NULL)
329
return p;
330
331
Error:
332
if (p -> SegInterp) _cmsFree(ContextID, p -> SegInterp);
333
if (p -> Segments) _cmsFree(ContextID, p -> Segments);
334
if (p -> Evals) _cmsFree(ContextID, p -> Evals);
335
if (p ->Table16) _cmsFree(ContextID, p ->Table16);
336
_cmsFree(ContextID, p);
337
return NULL;
338
}
339
340
341
// Parametric Fn using floating point
342
static
343
cmsFloat64Number DefaultEvalParametricFn(cmsInt32Number Type, const cmsFloat64Number Params[], cmsFloat64Number R)
344
{
345
cmsFloat64Number e, Val, disc;
346
347
switch (Type) {
348
349
// X = Y ^ Gamma
350
case 1:
351
if (R < 0) {
352
353
if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE)
354
Val = R;
355
else
356
Val = 0;
357
}
358
else
359
Val = pow(R, Params[0]);
360
break;
361
362
// Type 1 Reversed: X = Y ^1/gamma
363
case -1:
364
if (R < 0) {
365
366
if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE)
367
Val = R;
368
else
369
Val = 0;
370
}
371
else
372
{
373
if (fabs(Params[0]) < MATRIX_DET_TOLERANCE)
374
Val = PLUS_INF;
375
else
376
Val = pow(R, 1 / Params[0]);
377
}
378
break;
379
380
// CIE 122-1966
381
// Y = (aX + b)^Gamma | X >= -b/a
382
// Y = 0 | else
383
case 2:
384
{
385
386
if (fabs(Params[1]) < MATRIX_DET_TOLERANCE)
387
{
388
Val = 0;
389
}
390
else
391
{
392
disc = -Params[2] / Params[1];
393
394
if (R >= disc) {
395
396
e = Params[1] * R + Params[2];
397
398
if (e > 0)
399
Val = pow(e, Params[0]);
400
else
401
Val = 0;
402
}
403
else
404
Val = 0;
405
}
406
}
407
break;
408
409
// Type 2 Reversed
410
// X = (Y ^1/g - b) / a
411
case -2:
412
{
413
if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
414
fabs(Params[1]) < MATRIX_DET_TOLERANCE)
415
{
416
Val = 0;
417
}
418
else
419
{
420
if (R < 0)
421
Val = 0;
422
else
423
Val = (pow(R, 1.0 / Params[0]) - Params[2]) / Params[1];
424
425
if (Val < 0)
426
Val = 0;
427
}
428
}
429
break;
430
431
432
// IEC 61966-3
433
// Y = (aX + b)^Gamma | X <= -b/a
434
// Y = c | else
435
case 3:
436
{
437
if (fabs(Params[1]) < MATRIX_DET_TOLERANCE)
438
{
439
Val = 0;
440
}
441
else
442
{
443
disc = -Params[2] / Params[1];
444
if (disc < 0)
445
disc = 0;
446
447
if (R >= disc) {
448
449
e = Params[1] * R + Params[2];
450
451
if (e > 0)
452
Val = pow(e, Params[0]) + Params[3];
453
else
454
Val = 0;
455
}
456
else
457
Val = Params[3];
458
}
459
}
460
break;
461
462
463
// Type 3 reversed
464
// X=((Y-c)^1/g - b)/a | (Y>=c)
465
// X=-b/a | (Y<c)
466
case -3:
467
{
468
if (fabs(Params[1]) < MATRIX_DET_TOLERANCE)
469
{
470
Val = 0;
471
}
472
else
473
{
474
if (R >= Params[3]) {
475
476
e = R - Params[3];
477
478
if (e > 0)
479
Val = (pow(e, 1 / Params[0]) - Params[2]) / Params[1];
480
else
481
Val = 0;
482
}
483
else {
484
Val = -Params[2] / Params[1];
485
}
486
}
487
}
488
break;
489
490
491
// IEC 61966-2.1 (sRGB)
492
// Y = (aX + b)^Gamma | X >= d
493
// Y = cX | X < d
494
case 4:
495
if (R >= Params[4]) {
496
497
e = Params[1]*R + Params[2];
498
499
if (e > 0)
500
Val = pow(e, Params[0]);
501
else
502
Val = 0;
503
}
504
else
505
Val = R * Params[3];
506
break;
507
508
// Type 4 reversed
509
// X=((Y^1/g-b)/a) | Y >= (ad+b)^g
510
// X=Y/c | Y< (ad+b)^g
511
case -4:
512
{
513
if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
514
fabs(Params[1]) < MATRIX_DET_TOLERANCE ||
515
fabs(Params[3]) < MATRIX_DET_TOLERANCE)
516
{
517
Val = 0;
518
}
519
else
520
{
521
e = Params[1] * Params[4] + Params[2];
522
if (e < 0)
523
disc = 0;
524
else
525
disc = pow(e, Params[0]);
526
527
if (R >= disc) {
528
529
Val = (pow(R, 1.0 / Params[0]) - Params[2]) / Params[1];
530
}
531
else {
532
Val = R / Params[3];
533
}
534
}
535
}
536
break;
537
538
539
// Y = (aX + b)^Gamma + e | X >= d
540
// Y = cX + f | X < d
541
case 5:
542
if (R >= Params[4]) {
543
544
e = Params[1]*R + Params[2];
545
546
if (e > 0)
547
Val = pow(e, Params[0]) + Params[5];
548
else
549
Val = Params[5];
550
}
551
else
552
Val = R*Params[3] + Params[6];
553
break;
554
555
556
// Reversed type 5
557
// X=((Y-e)1/g-b)/a | Y >=(ad+b)^g+e), cd+f
558
// X=(Y-f)/c | else
559
case -5:
560
{
561
if (fabs(Params[1]) < MATRIX_DET_TOLERANCE ||
562
fabs(Params[3]) < MATRIX_DET_TOLERANCE)
563
{
564
Val = 0;
565
}
566
else
567
{
568
disc = Params[3] * Params[4] + Params[6];
569
if (R >= disc) {
570
571
e = R - Params[5];
572
if (e < 0)
573
Val = 0;
574
else
575
Val = (pow(e, 1.0 / Params[0]) - Params[2]) / Params[1];
576
}
577
else {
578
Val = (R - Params[6]) / Params[3];
579
}
580
}
581
}
582
break;
583
584
585
// Types 6,7,8 comes from segmented curves as described in ICCSpecRevision_02_11_06_Float.pdf
586
// Type 6 is basically identical to type 5 without d
587
588
// Y = (a * X + b) ^ Gamma + c
589
case 6:
590
e = Params[1]*R + Params[2];
591
592
if (e < 0)
593
Val = Params[3];
594
else
595
Val = pow(e, Params[0]) + Params[3];
596
break;
597
598
// ((Y - c) ^1/Gamma - b) / a
599
case -6:
600
{
601
if (fabs(Params[1]) < MATRIX_DET_TOLERANCE)
602
{
603
Val = 0;
604
}
605
else
606
{
607
e = R - Params[3];
608
if (e < 0)
609
Val = 0;
610
else
611
Val = (pow(e, 1.0 / Params[0]) - Params[2]) / Params[1];
612
}
613
}
614
break;
615
616
617
// Y = a * log (b * X^Gamma + c) + d
618
case 7:
619
620
e = Params[2] * pow(R, Params[0]) + Params[3];
621
if (e <= 0)
622
Val = Params[4];
623
else
624
Val = Params[1]*log10(e) + Params[4];
625
break;
626
627
// (Y - d) / a = log(b * X ^Gamma + c)
628
// pow(10, (Y-d) / a) = b * X ^Gamma + c
629
// pow((pow(10, (Y-d) / a) - c) / b, 1/g) = X
630
case -7:
631
{
632
if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
633
fabs(Params[1]) < MATRIX_DET_TOLERANCE ||
634
fabs(Params[2]) < MATRIX_DET_TOLERANCE)
635
{
636
Val = 0;
637
}
638
else
639
{
640
Val = pow((pow(10.0, (R - Params[4]) / Params[1]) - Params[3]) / Params[2], 1.0 / Params[0]);
641
}
642
}
643
break;
644
645
646
//Y = a * b^(c*X+d) + e
647
case 8:
648
Val = (Params[0] * pow(Params[1], Params[2] * R + Params[3]) + Params[4]);
649
break;
650
651
652
// Y = (log((y-e) / a) / log(b) - d ) / c
653
// a=0, b=1, c=2, d=3, e=4,
654
case -8:
655
656
disc = R - Params[4];
657
if (disc < 0) Val = 0;
658
else
659
{
660
if (fabs(Params[0]) < MATRIX_DET_TOLERANCE ||
661
fabs(Params[2]) < MATRIX_DET_TOLERANCE)
662
{
663
Val = 0;
664
}
665
else
666
{
667
Val = (log(disc / Params[0]) / log(Params[1]) - Params[3]) / Params[2];
668
}
669
}
670
break;
671
672
// S-Shaped: (1 - (1-x)^1/g)^1/g
673
case 108:
674
if (fabs(Params[0]) < MATRIX_DET_TOLERANCE)
675
Val = 0;
676
else
677
Val = pow(1.0 - pow(1 - R, 1/Params[0]), 1/Params[0]);
678
break;
679
680
// y = (1 - (1-x)^1/g)^1/g
681
// y^g = (1 - (1-x)^1/g)
682
// 1 - y^g = (1-x)^1/g
683
// (1 - y^g)^g = 1 - x
684
// 1 - (1 - y^g)^g
685
case -108:
686
Val = 1 - pow(1 - pow(R, Params[0]), Params[0]);
687
break;
688
689
default:
690
// Unsupported parametric curve. Should never reach here
691
return 0;
692
}
693
694
return Val;
695
}
696
697
// Evaluate a segmented function for a single value. Return -Inf if no valid segment found .
698
// If fn type is 0, perform an interpolation on the table
699
static
700
cmsFloat64Number EvalSegmentedFn(const cmsToneCurve *g, cmsFloat64Number R)
701
{
702
int i;
703
cmsFloat32Number Out32;
704
cmsFloat64Number Out;
705
706
for (i = (int) g->nSegments - 1; i >= 0; --i) {
707
708
// Check for domain
709
if ((R > g->Segments[i].x0) && (R <= g->Segments[i].x1)) {
710
711
// Type == 0 means segment is sampled
712
if (g->Segments[i].Type == 0) {
713
714
cmsFloat32Number R1 = (cmsFloat32Number)(R - g->Segments[i].x0) / (g->Segments[i].x1 - g->Segments[i].x0);
715
716
// Setup the table (TODO: clean that)
717
g->SegInterp[i]->Table = g->Segments[i].SampledPoints;
718
719
g->SegInterp[i]->Interpolation.LerpFloat(&R1, &Out32, g->SegInterp[i]);
720
Out = (cmsFloat64Number) Out32;
721
722
}
723
else {
724
Out = g->Evals[i](g->Segments[i].Type, g->Segments[i].Params, R);
725
}
726
727
if (isinf(Out))
728
return PLUS_INF;
729
else
730
{
731
if (isinf(-Out))
732
return MINUS_INF;
733
}
734
735
return Out;
736
}
737
}
738
739
return MINUS_INF;
740
}
741
742
// Access to estimated low-res table
743
cmsUInt32Number CMSEXPORT cmsGetToneCurveEstimatedTableEntries(const cmsToneCurve* t)
744
{
745
_cmsAssert(t != NULL);
746
return t ->nEntries;
747
}
748
749
const cmsUInt16Number* CMSEXPORT cmsGetToneCurveEstimatedTable(const cmsToneCurve* t)
750
{
751
_cmsAssert(t != NULL);
752
return t ->Table16;
753
}
754
755
756
// Create an empty gamma curve, by using tables. This specifies only the limited-precision part, and leaves the
757
// floating point description empty.
758
cmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurve16(cmsContext ContextID, cmsUInt32Number nEntries, const cmsUInt16Number Values[])
759
{
760
return AllocateToneCurveStruct(ContextID, nEntries, 0, NULL, Values);
761
}
762
763
static
764
cmsUInt32Number EntriesByGamma(cmsFloat64Number Gamma)
765
{
766
if (fabs(Gamma - 1.0) < 0.001) return 2;
767
return 4096;
768
}
769
770
771
// Create a segmented gamma, fill the table
772
cmsToneCurve* CMSEXPORT cmsBuildSegmentedToneCurve(cmsContext ContextID,
773
cmsUInt32Number nSegments, const cmsCurveSegment Segments[])
774
{
775
cmsUInt32Number i;
776
cmsFloat64Number R, Val;
777
cmsToneCurve* g;
778
cmsUInt32Number nGridPoints = 4096;
779
780
_cmsAssert(Segments != NULL);
781
782
// Optimizatin for identity curves.
783
if (nSegments == 1 && Segments[0].Type == 1) {
784
785
nGridPoints = EntriesByGamma(Segments[0].Params[0]);
786
}
787
788
g = AllocateToneCurveStruct(ContextID, nGridPoints, nSegments, Segments, NULL);
789
if (g == NULL) return NULL;
790
791
// Once we have the floating point version, we can approximate a 16 bit table of 4096 entries
792
// for performance reasons. This table would normally not be used except on 8/16 bits transforms.
793
for (i = 0; i < nGridPoints; i++) {
794
795
R = (cmsFloat64Number) i / (nGridPoints-1);
796
797
Val = EvalSegmentedFn(g, R);
798
799
// Round and saturate
800
g ->Table16[i] = _cmsQuickSaturateWord(Val * 65535.0);
801
}
802
803
return g;
804
}
805
806
// Use a segmented curve to store the floating point table
807
cmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurveFloat(cmsContext ContextID, cmsUInt32Number nEntries, const cmsFloat32Number values[])
808
{
809
cmsCurveSegment Seg[3];
810
811
// A segmented tone curve should have function segments in the first and last positions
812
// Initialize segmented curve part up to 0 to constant value = samples[0]
813
Seg[0].x0 = MINUS_INF;
814
Seg[0].x1 = 0;
815
Seg[0].Type = 6;
816
817
Seg[0].Params[0] = 1;
818
Seg[0].Params[1] = 0;
819
Seg[0].Params[2] = 0;
820
Seg[0].Params[3] = values[0];
821
Seg[0].Params[4] = 0;
822
823
// From zero to 1
824
Seg[1].x0 = 0;
825
Seg[1].x1 = 1.0;
826
Seg[1].Type = 0;
827
828
Seg[1].nGridPoints = nEntries;
829
Seg[1].SampledPoints = (cmsFloat32Number*) values;
830
831
// Final segment is constant = lastsample
832
Seg[2].x0 = 1.0;
833
Seg[2].x1 = PLUS_INF;
834
Seg[2].Type = 6;
835
836
Seg[2].Params[0] = 1;
837
Seg[2].Params[1] = 0;
838
Seg[2].Params[2] = 0;
839
Seg[2].Params[3] = values[nEntries-1];
840
Seg[2].Params[4] = 0;
841
842
843
return cmsBuildSegmentedToneCurve(ContextID, 3, Seg);
844
}
845
846
// Parametric curves
847
//
848
// Parameters goes as: Curve, a, b, c, d, e, f
849
// Type is the ICC type +1
850
// if type is negative, then the curve is analytically inverted
851
cmsToneCurve* CMSEXPORT cmsBuildParametricToneCurve(cmsContext ContextID, cmsInt32Number Type, const cmsFloat64Number Params[])
852
{
853
cmsCurveSegment Seg0;
854
int Pos = 0;
855
cmsUInt32Number size;
856
_cmsParametricCurvesCollection* c = GetParametricCurveByType(ContextID, Type, &Pos);
857
858
_cmsAssert(Params != NULL);
859
860
if (c == NULL) {
861
cmsSignalError(ContextID, cmsERROR_UNKNOWN_EXTENSION, "Invalid parametric curve type %d", Type);
862
return NULL;
863
}
864
865
memset(&Seg0, 0, sizeof(Seg0));
866
867
Seg0.x0 = MINUS_INF;
868
Seg0.x1 = PLUS_INF;
869
Seg0.Type = Type;
870
871
size = c->ParameterCount[Pos] * sizeof(cmsFloat64Number);
872
memmove(Seg0.Params, Params, size);
873
874
return cmsBuildSegmentedToneCurve(ContextID, 1, &Seg0);
875
}
876
877
878
879
// Build a gamma table based on gamma constant
880
cmsToneCurve* CMSEXPORT cmsBuildGamma(cmsContext ContextID, cmsFloat64Number Gamma)
881
{
882
return cmsBuildParametricToneCurve(ContextID, 1, &Gamma);
883
}
884
885
886
// Free all memory taken by the gamma curve
887
void CMSEXPORT cmsFreeToneCurve(cmsToneCurve* Curve)
888
{
889
cmsContext ContextID;
890
891
if (Curve == NULL) return;
892
893
ContextID = Curve ->InterpParams->ContextID;
894
895
_cmsFreeInterpParams(Curve ->InterpParams);
896
897
if (Curve -> Table16)
898
_cmsFree(ContextID, Curve ->Table16);
899
900
if (Curve ->Segments) {
901
902
cmsUInt32Number i;
903
904
for (i=0; i < Curve ->nSegments; i++) {
905
906
if (Curve ->Segments[i].SampledPoints) {
907
_cmsFree(ContextID, Curve ->Segments[i].SampledPoints);
908
}
909
910
if (Curve ->SegInterp[i] != 0)
911
_cmsFreeInterpParams(Curve->SegInterp[i]);
912
}
913
914
_cmsFree(ContextID, Curve ->Segments);
915
_cmsFree(ContextID, Curve ->SegInterp);
916
}
917
918
if (Curve -> Evals)
919
_cmsFree(ContextID, Curve -> Evals);
920
921
_cmsFree(ContextID, Curve);
922
}
923
924
// Utility function, free 3 gamma tables
925
void CMSEXPORT cmsFreeToneCurveTriple(cmsToneCurve* Curve[3])
926
{
927
928
_cmsAssert(Curve != NULL);
929
930
if (Curve[0] != NULL) cmsFreeToneCurve(Curve[0]);
931
if (Curve[1] != NULL) cmsFreeToneCurve(Curve[1]);
932
if (Curve[2] != NULL) cmsFreeToneCurve(Curve[2]);
933
934
Curve[0] = Curve[1] = Curve[2] = NULL;
935
}
936
937
938
// Duplicate a gamma table
939
cmsToneCurve* CMSEXPORT cmsDupToneCurve(const cmsToneCurve* In)
940
{
941
if (In == NULL) return NULL;
942
943
return AllocateToneCurveStruct(In ->InterpParams ->ContextID, In ->nEntries, In ->nSegments, In ->Segments, In ->Table16);
944
}
945
946
// Joins two curves for X and Y. Curves should be monotonic.
947
// We want to get
948
//
949
// y = Y^-1(X(t))
950
//
951
cmsToneCurve* CMSEXPORT cmsJoinToneCurve(cmsContext ContextID,
952
const cmsToneCurve* X,
953
const cmsToneCurve* Y, cmsUInt32Number nResultingPoints)
954
{
955
cmsToneCurve* out = NULL;
956
cmsToneCurve* Yreversed = NULL;
957
cmsFloat32Number t, x;
958
cmsFloat32Number* Res = NULL;
959
cmsUInt32Number i;
960
961
962
_cmsAssert(X != NULL);
963
_cmsAssert(Y != NULL);
964
965
Yreversed = cmsReverseToneCurveEx(nResultingPoints, Y);
966
if (Yreversed == NULL) goto Error;
967
968
Res = (cmsFloat32Number*) _cmsCalloc(ContextID, nResultingPoints, sizeof(cmsFloat32Number));
969
if (Res == NULL) goto Error;
970
971
//Iterate
972
for (i=0; i < nResultingPoints; i++) {
973
974
t = (cmsFloat32Number) i / (nResultingPoints-1);
975
x = cmsEvalToneCurveFloat(X, t);
976
Res[i] = cmsEvalToneCurveFloat(Yreversed, x);
977
}
978
979
// Allocate space for output
980
out = cmsBuildTabulatedToneCurveFloat(ContextID, nResultingPoints, Res);
981
982
Error:
983
984
if (Res != NULL) _cmsFree(ContextID, Res);
985
if (Yreversed != NULL) cmsFreeToneCurve(Yreversed);
986
987
return out;
988
}
989
990
991
992
// Get the surrounding nodes. This is tricky on non-monotonic tables
993
static
994
int GetInterval(cmsFloat64Number In, const cmsUInt16Number LutTable[], const struct _cms_interp_struc* p)
995
{
996
int i;
997
int y0, y1;
998
999
// A 1 point table is not allowed
1000
if (p -> Domain[0] < 1) return -1;
1001
1002
// Let's see if ascending or descending.
1003
if (LutTable[0] < LutTable[p ->Domain[0]]) {
1004
1005
// Table is overall ascending
1006
for (i = (int) p->Domain[0] - 1; i >= 0; --i) {
1007
1008
y0 = LutTable[i];
1009
y1 = LutTable[i+1];
1010
1011
if (y0 <= y1) { // Increasing
1012
if (In >= y0 && In <= y1) return i;
1013
}
1014
else
1015
if (y1 < y0) { // Decreasing
1016
if (In >= y1 && In <= y0) return i;
1017
}
1018
}
1019
}
1020
else {
1021
// Table is overall descending
1022
for (i=0; i < (int) p -> Domain[0]; i++) {
1023
1024
y0 = LutTable[i];
1025
y1 = LutTable[i+1];
1026
1027
if (y0 <= y1) { // Increasing
1028
if (In >= y0 && In <= y1) return i;
1029
}
1030
else
1031
if (y1 < y0) { // Decreasing
1032
if (In >= y1 && In <= y0) return i;
1033
}
1034
}
1035
}
1036
1037
return -1;
1038
}
1039
1040
// Reverse a gamma table
1041
cmsToneCurve* CMSEXPORT cmsReverseToneCurveEx(cmsUInt32Number nResultSamples, const cmsToneCurve* InCurve)
1042
{
1043
cmsToneCurve *out;
1044
cmsFloat64Number a = 0, b = 0, y, x1, y1, x2, y2;
1045
int i, j;
1046
int Ascending;
1047
1048
_cmsAssert(InCurve != NULL);
1049
1050
// Try to reverse it analytically whatever possible
1051
1052
if (InCurve ->nSegments == 1 && InCurve ->Segments[0].Type > 0 &&
1053
/* InCurve -> Segments[0].Type <= 5 */
1054
GetParametricCurveByType(InCurve ->InterpParams->ContextID, InCurve ->Segments[0].Type, NULL) != NULL) {
1055
1056
return cmsBuildParametricToneCurve(InCurve ->InterpParams->ContextID,
1057
-(InCurve -> Segments[0].Type),
1058
InCurve -> Segments[0].Params);
1059
}
1060
1061
// Nope, reverse the table.
1062
out = cmsBuildTabulatedToneCurve16(InCurve ->InterpParams->ContextID, nResultSamples, NULL);
1063
if (out == NULL)
1064
return NULL;
1065
1066
// We want to know if this is an ascending or descending table
1067
Ascending = !cmsIsToneCurveDescending(InCurve);
1068
1069
// Iterate across Y axis
1070
for (i=0; i < (int) nResultSamples; i++) {
1071
1072
y = (cmsFloat64Number) i * 65535.0 / (nResultSamples - 1);
1073
1074
// Find interval in which y is within.
1075
j = GetInterval(y, InCurve->Table16, InCurve->InterpParams);
1076
if (j >= 0) {
1077
1078
1079
// Get limits of interval
1080
x1 = InCurve ->Table16[j];
1081
x2 = InCurve ->Table16[j+1];
1082
1083
y1 = (cmsFloat64Number) (j * 65535.0) / (InCurve ->nEntries - 1);
1084
y2 = (cmsFloat64Number) ((j+1) * 65535.0 ) / (InCurve ->nEntries - 1);
1085
1086
// If collapsed, then use any
1087
if (x1 == x2) {
1088
1089
out ->Table16[i] = _cmsQuickSaturateWord(Ascending ? y2 : y1);
1090
continue;
1091
1092
} else {
1093
1094
// Interpolate
1095
a = (y2 - y1) / (x2 - x1);
1096
b = y2 - a * x2;
1097
}
1098
}
1099
1100
out ->Table16[i] = _cmsQuickSaturateWord(a* y + b);
1101
}
1102
1103
1104
return out;
1105
}
1106
1107
// Reverse a gamma table
1108
cmsToneCurve* CMSEXPORT cmsReverseToneCurve(const cmsToneCurve* InGamma)
1109
{
1110
_cmsAssert(InGamma != NULL);
1111
1112
return cmsReverseToneCurveEx(4096, InGamma);
1113
}
1114
1115
// From: Eilers, P.H.C. (1994) Smoothing and interpolation with finite
1116
// differences. in: Graphic Gems IV, Heckbert, P.S. (ed.), Academic press.
1117
//
1118
// Smoothing and interpolation with second differences.
1119
//
1120
// Input: weights (w), data (y): vector from 1 to m.
1121
// Input: smoothing parameter (lambda), length (m).
1122
// Output: smoothed vector (z): vector from 1 to m.
1123
1124
static
1125
cmsBool smooth2(cmsContext ContextID, cmsFloat32Number w[], cmsFloat32Number y[],
1126
cmsFloat32Number z[], cmsFloat32Number lambda, int m)
1127
{
1128
int i, i1, i2;
1129
cmsFloat32Number *c, *d, *e;
1130
cmsBool st;
1131
1132
1133
c = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number));
1134
d = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number));
1135
e = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number));
1136
1137
if (c != NULL && d != NULL && e != NULL) {
1138
1139
1140
d[1] = w[1] + lambda;
1141
c[1] = -2 * lambda / d[1];
1142
e[1] = lambda /d[1];
1143
z[1] = w[1] * y[1];
1144
d[2] = w[2] + 5 * lambda - d[1] * c[1] * c[1];
1145
c[2] = (-4 * lambda - d[1] * c[1] * e[1]) / d[2];
1146
e[2] = lambda / d[2];
1147
z[2] = w[2] * y[2] - c[1] * z[1];
1148
1149
for (i = 3; i < m - 1; i++) {
1150
i1 = i - 1; i2 = i - 2;
1151
d[i]= w[i] + 6 * lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2];
1152
c[i] = (-4 * lambda -d[i1] * c[i1] * e[i1])/ d[i];
1153
e[i] = lambda / d[i];
1154
z[i] = w[i] * y[i] - c[i1] * z[i1] - e[i2] * z[i2];
1155
}
1156
1157
i1 = m - 2; i2 = m - 3;
1158
1159
d[m - 1] = w[m - 1] + 5 * lambda -c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2];
1160
c[m - 1] = (-2 * lambda - d[i1] * c[i1] * e[i1]) / d[m - 1];
1161
z[m - 1] = w[m - 1] * y[m - 1] - c[i1] * z[i1] - e[i2] * z[i2];
1162
i1 = m - 1; i2 = m - 2;
1163
1164
d[m] = w[m] + lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2];
1165
z[m] = (w[m] * y[m] - c[i1] * z[i1] - e[i2] * z[i2]) / d[m];
1166
z[m - 1] = z[m - 1] / d[m - 1] - c[m - 1] * z[m];
1167
1168
for (i = m - 2; 1<= i; i--)
1169
z[i] = z[i] / d[i] - c[i] * z[i + 1] - e[i] * z[i + 2];
1170
1171
st = TRUE;
1172
}
1173
else st = FALSE;
1174
1175
if (c != NULL) _cmsFree(ContextID, c);
1176
if (d != NULL) _cmsFree(ContextID, d);
1177
if (e != NULL) _cmsFree(ContextID, e);
1178
1179
return st;
1180
}
1181
1182
// Smooths a curve sampled at regular intervals.
1183
cmsBool CMSEXPORT cmsSmoothToneCurve(cmsToneCurve* Tab, cmsFloat64Number lambda)
1184
{
1185
cmsBool SuccessStatus = TRUE;
1186
cmsFloat32Number *w, *y, *z;
1187
cmsUInt32Number i, nItems, Zeros, Poles;
1188
1189
if (Tab != NULL && Tab->InterpParams != NULL)
1190
{
1191
cmsContext ContextID = Tab->InterpParams->ContextID;
1192
1193
if (!cmsIsToneCurveLinear(Tab)) // Only non-linear curves need smoothing
1194
{
1195
nItems = Tab->nEntries;
1196
if (nItems < MAX_NODES_IN_CURVE)
1197
{
1198
// Allocate one more item than needed
1199
w = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number));
1200
y = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number));
1201
z = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number));
1202
1203
if (w != NULL && y != NULL && z != NULL) // Ensure no memory allocation failure
1204
{
1205
memset(w, 0, (nItems + 1) * sizeof(cmsFloat32Number));
1206
memset(y, 0, (nItems + 1) * sizeof(cmsFloat32Number));
1207
memset(z, 0, (nItems + 1) * sizeof(cmsFloat32Number));
1208
1209
for (i = 0; i < nItems; i++)
1210
{
1211
y[i + 1] = (cmsFloat32Number)Tab->Table16[i];
1212
w[i + 1] = 1.0;
1213
}
1214
1215
if (smooth2(ContextID, w, y, z, (cmsFloat32Number)lambda, (int)nItems))
1216
{
1217
// Do some reality - checking...
1218
1219
Zeros = Poles = 0;
1220
for (i = nItems; i > 1; --i)
1221
{
1222
if (z[i] == 0.) Zeros++;
1223
if (z[i] >= 65535.) Poles++;
1224
if (z[i] < z[i - 1])
1225
{
1226
cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Non-Monotonic.");
1227
SuccessStatus = FALSE;
1228
break;
1229
}
1230
}
1231
1232
if (SuccessStatus && Zeros > (nItems / 3))
1233
{
1234
cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly zeros.");
1235
SuccessStatus = FALSE;
1236
}
1237
1238
if (SuccessStatus && Poles > (nItems / 3))
1239
{
1240
cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly poles.");
1241
SuccessStatus = FALSE;
1242
}
1243
1244
if (SuccessStatus) // Seems ok
1245
{
1246
for (i = 0; i < nItems; i++)
1247
{
1248
// Clamp to cmsUInt16Number
1249
Tab->Table16[i] = _cmsQuickSaturateWord(z[i + 1]);
1250
}
1251
}
1252
}
1253
else // Could not smooth
1254
{
1255
cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Function smooth2 failed.");
1256
SuccessStatus = FALSE;
1257
}
1258
}
1259
else // One or more buffers could not be allocated
1260
{
1261
cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Could not allocate memory.");
1262
SuccessStatus = FALSE;
1263
}
1264
1265
if (z != NULL)
1266
_cmsFree(ContextID, z);
1267
1268
if (y != NULL)
1269
_cmsFree(ContextID, y);
1270
1271
if (w != NULL)
1272
_cmsFree(ContextID, w);
1273
}
1274
else // too many items in the table
1275
{
1276
cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Too many points.");
1277
SuccessStatus = FALSE;
1278
}
1279
}
1280
}
1281
else // Tab parameter or Tab->InterpParams is NULL
1282
{
1283
// Can't signal an error here since the ContextID is not known at this point
1284
SuccessStatus = FALSE;
1285
}
1286
1287
return SuccessStatus;
1288
}
1289
1290
// Is a table linear? Do not use parametric since we cannot guarantee some weird parameters resulting
1291
// in a linear table. This way assures it is linear in 12 bits, which should be enough in most cases.
1292
cmsBool CMSEXPORT cmsIsToneCurveLinear(const cmsToneCurve* Curve)
1293
{
1294
int i;
1295
int diff;
1296
1297
_cmsAssert(Curve != NULL);
1298
1299
for (i=0; i < (int) Curve ->nEntries; i++) {
1300
1301
diff = abs((int) Curve->Table16[i] - (int) _cmsQuantizeVal(i, Curve ->nEntries));
1302
if (diff > 0x0f)
1303
return FALSE;
1304
}
1305
1306
return TRUE;
1307
}
1308
1309
// Same, but for monotonicity
1310
cmsBool CMSEXPORT cmsIsToneCurveMonotonic(const cmsToneCurve* t)
1311
{
1312
cmsUInt32Number n;
1313
int i, last;
1314
cmsBool lDescending;
1315
1316
_cmsAssert(t != NULL);
1317
1318
// Degenerated curves are monotonic? Ok, let's pass them
1319
n = t ->nEntries;
1320
if (n < 2) return TRUE;
1321
1322
// Curve direction
1323
lDescending = cmsIsToneCurveDescending(t);
1324
1325
if (lDescending) {
1326
1327
last = t ->Table16[0];
1328
1329
for (i = 1; i < (int) n; i++) {
1330
1331
if (t ->Table16[i] - last > 2) // We allow some ripple
1332
return FALSE;
1333
else
1334
last = t ->Table16[i];
1335
1336
}
1337
}
1338
else {
1339
1340
last = t ->Table16[n-1];
1341
1342
for (i = (int) n - 2; i >= 0; --i) {
1343
1344
if (t ->Table16[i] - last > 2)
1345
return FALSE;
1346
else
1347
last = t ->Table16[i];
1348
1349
}
1350
}
1351
1352
return TRUE;
1353
}
1354
1355
// Same, but for descending tables
1356
cmsBool CMSEXPORT cmsIsToneCurveDescending(const cmsToneCurve* t)
1357
{
1358
_cmsAssert(t != NULL);
1359
1360
return t ->Table16[0] > t ->Table16[t ->nEntries-1];
1361
}
1362
1363
1364
// Another info fn: is out gamma table multisegment?
1365
cmsBool CMSEXPORT cmsIsToneCurveMultisegment(const cmsToneCurve* t)
1366
{
1367
_cmsAssert(t != NULL);
1368
1369
return t -> nSegments > 1;
1370
}
1371
1372
cmsInt32Number CMSEXPORT cmsGetToneCurveParametricType(const cmsToneCurve* t)
1373
{
1374
_cmsAssert(t != NULL);
1375
1376
if (t -> nSegments != 1) return 0;
1377
return t ->Segments[0].Type;
1378
}
1379
1380
// We need accuracy this time
1381
cmsFloat32Number CMSEXPORT cmsEvalToneCurveFloat(const cmsToneCurve* Curve, cmsFloat32Number v)
1382
{
1383
_cmsAssert(Curve != NULL);
1384
1385
// Check for 16 bits table. If so, this is a limited-precision tone curve
1386
if (Curve ->nSegments == 0) {
1387
1388
cmsUInt16Number In, Out;
1389
1390
In = (cmsUInt16Number) _cmsQuickSaturateWord(v * 65535.0);
1391
Out = cmsEvalToneCurve16(Curve, In);
1392
1393
return (cmsFloat32Number) (Out / 65535.0);
1394
}
1395
1396
return (cmsFloat32Number) EvalSegmentedFn(Curve, v);
1397
}
1398
1399
// We need xput over here
1400
cmsUInt16Number CMSEXPORT cmsEvalToneCurve16(const cmsToneCurve* Curve, cmsUInt16Number v)
1401
{
1402
cmsUInt16Number out;
1403
1404
_cmsAssert(Curve != NULL);
1405
1406
Curve ->InterpParams ->Interpolation.Lerp16(&v, &out, Curve ->InterpParams);
1407
return out;
1408
}
1409
1410
1411
// Least squares fitting.
1412
// A mathematical procedure for finding the best-fitting curve to a given set of points by
1413
// minimizing the sum of the squares of the offsets ("the residuals") of the points from the curve.
1414
// The sum of the squares of the offsets is used instead of the offset absolute values because
1415
// this allows the residuals to be treated as a continuous differentiable quantity.
1416
//
1417
// y = f(x) = x ^ g
1418
//
1419
// R = (yi - (xi^g))
1420
// R2 = (yi - (xi^g))2
1421
// SUM R2 = SUM (yi - (xi^g))2
1422
//
1423
// dR2/dg = -2 SUM x^g log(x)(y - x^g)
1424
// solving for dR2/dg = 0
1425
//
1426
// g = 1/n * SUM(log(y) / log(x))
1427
1428
cmsFloat64Number CMSEXPORT cmsEstimateGamma(const cmsToneCurve* t, cmsFloat64Number Precision)
1429
{
1430
cmsFloat64Number gamma, sum, sum2;
1431
cmsFloat64Number n, x, y, Std;
1432
cmsUInt32Number i;
1433
1434
_cmsAssert(t != NULL);
1435
1436
sum = sum2 = n = 0;
1437
1438
// Excluding endpoints
1439
for (i=1; i < (MAX_NODES_IN_CURVE-1); i++) {
1440
1441
x = (cmsFloat64Number) i / (MAX_NODES_IN_CURVE-1);
1442
y = (cmsFloat64Number) cmsEvalToneCurveFloat(t, (cmsFloat32Number) x);
1443
1444
// Avoid 7% on lower part to prevent
1445
// artifacts due to linear ramps
1446
1447
if (y > 0. && y < 1. && x > 0.07) {
1448
1449
gamma = log(y) / log(x);
1450
sum += gamma;
1451
sum2 += gamma * gamma;
1452
n++;
1453
}
1454
}
1455
1456
// Take a look on SD to see if gamma isn't exponential at all
1457
Std = sqrt((n * sum2 - sum * sum) / (n*(n-1)));
1458
1459
if (Std > Precision)
1460
return -1.0;
1461
1462
return (sum / n); // The mean
1463
}
1464
1465
1466
// Retrieve parameters on one-segment tone curves
1467
1468
cmsFloat64Number* CMSEXPORT cmsGetToneCurveParams(const cmsToneCurve* t)
1469
{
1470
_cmsAssert(t != NULL);
1471
1472
if (t->nSegments != 1) return NULL;
1473
return t->Segments[0].Params;
1474
}
1475
1476