1 //--------------------------------------------------------------------------------- 2 // 3 // Little Color Management System 4 // Copyright (c) 1998-2013 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 27 #include "lcms2_internal.h" 28 29 // Tone curves are powerful constructs that can contain curves specified in diverse ways. 30 // The curve is stored in segments, where each segment can be sampled or specified by parameters. 31 // a 16.bit simplification of the *whole* curve is kept for optimization purposes. For float operation, 32 // each segment is evaluated separately. Plug-ins may be used to define new parametric schemes, 33 // each plug-in may define up to MAX_TYPES_IN_LCMS_PLUGIN functions types. For defining a function, 34 // the plug-in should provide the type id, how many parameters each type has, and a pointer to 35 // a procedure that evaluates the function. In the case of reverse evaluation, the evaluator will 36 // be called with the type id as a negative value, and a sampled version of the reversed curve 37 // will be built. 38 39 // ----------------------------------------------------------------- Implementation 40 // Maxim number of nodes 41 #define MAX_NODES_IN_CURVE 4097 42 #define MINUS_INF (-1E22F) 43 #define PLUS_INF (+1E22F) 44 45 // The list of supported parametric curves 46 typedef struct _cmsParametricCurvesCollection_st { 47 48 int nFunctions; // Number of supported functions in this chunk 49 int FunctionTypes[MAX_TYPES_IN_LCMS_PLUGIN]; // The identification types 50 int ParameterCount[MAX_TYPES_IN_LCMS_PLUGIN]; // Number of parameters for each function 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 _cmsParametricCurvesCollection DefaultCurves = { 62 9, // # of curve types 63 { 1, 2, 3, 4, 5, 6, 7, 8, 108 }, // Parametric curve ID 64 { 1, 3, 4, 5, 7, 4, 5, 5, 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 < 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 optimation 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, cmsInt32Number nEntries, 214 cmsInt32Number nSegments, const cmsCurveSegment* Segments, 215 const cmsUInt16Number* Values) 216 { 217 cmsToneCurve* p; 218 int i; 219 220 // We allow huge tables, which are then restricted for smoothing operations 221 if (nEntries > 65530 || nEntries < 0) { 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 if (p -> Segments) _cmsFree(ContextID, p ->Segments); 304 if (p -> Evals) _cmsFree(ContextID, p -> Evals); 305 if (p ->Table16) _cmsFree(ContextID, p ->Table16); 306 _cmsFree(ContextID, p); 307 return NULL; 308 } 309 310 311 // Parametric Fn using floating point 312 static 313 cmsFloat64Number DefaultEvalParametricFn(cmsInt32Number Type, const cmsFloat64Number Params[], cmsFloat64Number R) 314 { 315 cmsFloat64Number e, Val, disc; 316 317 switch (Type) { 318 319 // X = Y ^ Gamma 320 case 1: 321 if (R < 0) { 322 323 if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE) 324 Val = R; 325 else 326 Val = 0; 327 } 328 else 329 Val = pow(R, Params[0]); 330 break; 331 332 // Type 1 Reversed: X = Y ^1/gamma 333 case -1: 334 if (R < 0) { 335 336 if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE) 337 Val = R; 338 else 339 Val = 0; 340 } 341 else 342 Val = pow(R, 1/Params[0]); 343 break; 344 345 // CIE 122-1966 346 // Y = (aX + b)^Gamma | X >= -b/a 347 // Y = 0 | else 348 case 2: 349 disc = -Params[2] / Params[1]; 350 351 if (R >= disc ) { 352 353 e = Params[1]*R + Params[2]; 354 355 if (e > 0) 356 Val = pow(e, Params[0]); 357 else 358 Val = 0; 359 } 360 else 361 Val = 0; 362 break; 363 364 // Type 2 Reversed 365 // X = (Y ^1/g - b) / a 366 case -2: 367 if (R < 0) 368 Val = 0; 369 else 370 Val = (pow(R, 1.0/Params[0]) - Params[2]) / Params[1]; 371 372 if (Val < 0) 373 Val = 0; 374 break; 375 376 377 // IEC 61966-3 378 // Y = (aX + b)^Gamma | X <= -b/a 379 // Y = c | else 380 case 3: 381 disc = -Params[2] / Params[1]; 382 if (disc < 0) 383 disc = 0; 384 385 if (R >= disc) { 386 387 e = Params[1]*R + Params[2]; 388 389 if (e > 0) 390 Val = pow(e, Params[0]) + Params[3]; 391 else 392 Val = 0; 393 } 394 else 395 Val = Params[3]; 396 break; 397 398 399 // Type 3 reversed 400 // X=((Y-c)^1/g - b)/a | (Y>=c) 401 // X=-b/a | (Y<c) 402 case -3: 403 if (R >= Params[3]) { 404 405 e = R - Params[3]; 406 407 if (e > 0) 408 Val = (pow(e, 1/Params[0]) - Params[2]) / Params[1]; 409 else 410 Val = 0; 411 } 412 else { 413 Val = -Params[2] / Params[1]; 414 } 415 break; 416 417 418 // IEC 61966-2.1 (sRGB) 419 // Y = (aX + b)^Gamma | X >= d 420 // Y = cX | X < d 421 case 4: 422 if (R >= Params[4]) { 423 424 e = Params[1]*R + Params[2]; 425 426 if (e > 0) 427 Val = pow(e, Params[0]); 428 else 429 Val = 0; 430 } 431 else 432 Val = R * Params[3]; 433 break; 434 435 // Type 4 reversed 436 // X=((Y^1/g-b)/a) | Y >= (ad+b)^g 437 // X=Y/c | Y< (ad+b)^g 438 case -4: 439 e = Params[1] * Params[4] + Params[2]; 440 if (e < 0) 441 disc = 0; 442 else 443 disc = pow(e, Params[0]); 444 445 if (R >= disc) { 446 447 Val = (pow(R, 1.0/Params[0]) - Params[2]) / Params[1]; 448 } 449 else { 450 Val = R / Params[3]; 451 } 452 break; 453 454 455 // Y = (aX + b)^Gamma + e | X >= d 456 // Y = cX + f | X < d 457 case 5: 458 if (R >= Params[4]) { 459 460 e = Params[1]*R + Params[2]; 461 462 if (e > 0) 463 Val = pow(e, Params[0]) + Params[5]; 464 else 465 Val = Params[5]; 466 } 467 else 468 Val = R*Params[3] + Params[6]; 469 break; 470 471 472 // Reversed type 5 473 // X=((Y-e)1/g-b)/a | Y >=(ad+b)^g+e), cd+f 474 // X=(Y-f)/c | else 475 case -5: 476 477 disc = Params[3] * Params[4] + Params[6]; 478 if (R >= disc) { 479 480 e = R - Params[5]; 481 if (e < 0) 482 Val = 0; 483 else 484 Val = (pow(e, 1.0/Params[0]) - Params[2]) / Params[1]; 485 } 486 else { 487 Val = (R - Params[6]) / Params[3]; 488 } 489 break; 490 491 492 // Types 6,7,8 comes from segmented curves as described in ICCSpecRevision_02_11_06_Float.pdf 493 // Type 6 is basically identical to type 5 without d 494 495 // Y = (a * X + b) ^ Gamma + c 496 case 6: 497 e = Params[1]*R + Params[2]; 498 499 if (e < 0) 500 Val = Params[3]; 501 else 502 Val = pow(e, Params[0]) + Params[3]; 503 break; 504 505 // ((Y - c) ^1/Gamma - b) / a 506 case -6: 507 e = R - Params[3]; 508 if (e < 0) 509 Val = 0; 510 else 511 Val = (pow(e, 1.0/Params[0]) - Params[2]) / Params[1]; 512 break; 513 514 515 // Y = a * log (b * X^Gamma + c) + d 516 case 7: 517 518 e = Params[2] * pow(R, Params[0]) + Params[3]; 519 if (e <= 0) 520 Val = Params[4]; 521 else 522 Val = Params[1]*log10(e) + Params[4]; 523 break; 524 525 // (Y - d) / a = log(b * X ^Gamma + c) 526 // pow(10, (Y-d) / a) = b * X ^Gamma + c 527 // pow((pow(10, (Y-d) / a) - c) / b, 1/g) = X 528 case -7: 529 Val = pow((pow(10.0, (R-Params[4]) / Params[1]) - Params[3]) / Params[2], 1.0 / Params[0]); 530 break; 531 532 533 //Y = a * b^(c*X+d) + e 534 case 8: 535 Val = (Params[0] * pow(Params[1], Params[2] * R + Params[3]) + Params[4]); 536 break; 537 538 539 // Y = (log((y-e) / a) / log(b) - d ) / c 540 // a=0, b=1, c=2, d=3, e=4, 541 case -8: 542 543 disc = R - Params[4]; 544 if (disc < 0) Val = 0; 545 else 546 Val = (log(disc / Params[0]) / log(Params[1]) - Params[3]) / Params[2]; 547 break; 548 549 // S-Shaped: (1 - (1-x)^1/g)^1/g 550 case 108: 551 Val = pow(1.0 - pow(1 - R, 1/Params[0]), 1/Params[0]); 552 break; 553 554 // y = (1 - (1-x)^1/g)^1/g 555 // y^g = (1 - (1-x)^1/g) 556 // 1 - y^g = (1-x)^1/g 557 // (1 - y^g)^g = 1 - x 558 // 1 - (1 - y^g)^g 559 case -108: 560 Val = 1 - pow(1 - pow(R, Params[0]), Params[0]); 561 break; 562 563 default: 564 // Unsupported parametric curve. Should never reach here 565 return 0; 566 } 567 568 return Val; 569 } 570 571 // Evaluate a segmented funtion for a single value. Return -1 if no valid segment found . 572 // If fn type is 0, perform an interpolation on the table 573 static 574 cmsFloat64Number EvalSegmentedFn(const cmsToneCurve *g, cmsFloat64Number R) 575 { 576 int i; 577 578 for (i = g ->nSegments-1; i >= 0 ; --i) { 579 580 // Check for domain 581 if ((R > g ->Segments[i].x0) && (R <= g ->Segments[i].x1)) { 582 583 // Type == 0 means segment is sampled 584 if (g ->Segments[i].Type == 0) { 585 586 cmsFloat32Number R1 = (cmsFloat32Number) (R - g ->Segments[i].x0) / (g ->Segments[i].x1 - g ->Segments[i].x0); 587 cmsFloat32Number Out; 588 589 // Setup the table (TODO: clean that) 590 g ->SegInterp[i]-> Table = g ->Segments[i].SampledPoints; 591 592 g ->SegInterp[i] -> Interpolation.LerpFloat(&R1, &Out, g ->SegInterp[i]); 593 594 return Out; 595 } 596 else 597 return g ->Evals[i](g->Segments[i].Type, g ->Segments[i].Params, R); 598 } 599 } 600 601 return MINUS_INF; 602 } 603 604 // Access to estimated low-res table 605 cmsUInt32Number CMSEXPORT cmsGetToneCurveEstimatedTableEntries(const cmsToneCurve* t) 606 { 607 _cmsAssert(t != NULL); 608 return t ->nEntries; 609 } 610 611 const cmsUInt16Number* CMSEXPORT cmsGetToneCurveEstimatedTable(const cmsToneCurve* t) 612 { 613 _cmsAssert(t != NULL); 614 return t ->Table16; 615 } 616 617 618 // Create an empty gamma curve, by using tables. This specifies only the limited-precision part, and leaves the 619 // floating point description empty. 620 cmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurve16(cmsContext ContextID, cmsInt32Number nEntries, const cmsUInt16Number Values[]) 621 { 622 return AllocateToneCurveStruct(ContextID, nEntries, 0, NULL, Values); 623 } 624 625 static 626 int EntriesByGamma(cmsFloat64Number Gamma) 627 { 628 if (fabs(Gamma - 1.0) < 0.001) return 2; 629 return 4096; 630 } 631 632 633 // Create a segmented gamma, fill the table 634 cmsToneCurve* CMSEXPORT cmsBuildSegmentedToneCurve(cmsContext ContextID, 635 cmsInt32Number nSegments, const cmsCurveSegment Segments[]) 636 { 637 int i; 638 cmsFloat64Number R, Val; 639 cmsToneCurve* g; 640 int nGridPoints = 4096; 641 642 _cmsAssert(Segments != NULL); 643 644 // Optimizatin for identity curves. 645 if (nSegments == 1 && Segments[0].Type == 1) { 646 647 nGridPoints = EntriesByGamma(Segments[0].Params[0]); 648 } 649 650 g = AllocateToneCurveStruct(ContextID, nGridPoints, nSegments, Segments, NULL); 651 if (g == NULL) return NULL; 652 653 // Once we have the floating point version, we can approximate a 16 bit table of 4096 entries 654 // for performance reasons. This table would normally not be used except on 8/16 bits transforms. 655 for (i=0; i < nGridPoints; i++) { 656 657 R = (cmsFloat64Number) i / (nGridPoints-1); 658 659 Val = EvalSegmentedFn(g, R); 660 661 // Round and saturate 662 g ->Table16[i] = _cmsQuickSaturateWord(Val * 65535.0); 663 } 664 665 return g; 666 } 667 668 // Use a segmented curve to store the floating point table 669 cmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurveFloat(cmsContext ContextID, cmsUInt32Number nEntries, const cmsFloat32Number values[]) 670 { 671 cmsCurveSegment Seg[3]; 672 673 // A segmented tone curve should have function segments in the first and last positions 674 // Initialize segmented curve part up to 0 to constant value = samples[0] 675 Seg[0].x0 = MINUS_INF; 676 Seg[0].x1 = 0; 677 Seg[0].Type = 6; 678 679 Seg[0].Params[0] = 1; 680 Seg[0].Params[1] = 0; 681 Seg[0].Params[2] = 0; 682 Seg[0].Params[3] = values[0]; 683 Seg[0].Params[4] = 0; 684 685 // From zero to 1 686 Seg[1].x0 = 0; 687 Seg[1].x1 = 1.0; 688 Seg[1].Type = 0; 689 690 Seg[1].nGridPoints = nEntries; 691 Seg[1].SampledPoints = (cmsFloat32Number*) values; 692 693 // Final segment is constant = lastsample 694 Seg[2].x0 = 1.0; 695 Seg[2].x1 = PLUS_INF; 696 Seg[2].Type = 6; 697 698 Seg[2].Params[0] = 1; 699 Seg[2].Params[1] = 0; 700 Seg[2].Params[2] = 0; 701 Seg[2].Params[3] = values[nEntries-1]; 702 Seg[2].Params[4] = 0; 703 704 705 return cmsBuildSegmentedToneCurve(ContextID, 3, Seg); 706 } 707 708 // Parametric curves 709 // 710 // Parameters goes as: Curve, a, b, c, d, e, f 711 // Type is the ICC type +1 712 // if type is negative, then the curve is analyticaly inverted 713 cmsToneCurve* CMSEXPORT cmsBuildParametricToneCurve(cmsContext ContextID, cmsInt32Number Type, const cmsFloat64Number Params[]) 714 { 715 cmsCurveSegment Seg0; 716 int Pos = 0; 717 cmsUInt32Number size; 718 _cmsParametricCurvesCollection* c = GetParametricCurveByType(ContextID, Type, &Pos); 719 720 _cmsAssert(Params != NULL); 721 722 if (c == NULL) { 723 cmsSignalError(ContextID, cmsERROR_UNKNOWN_EXTENSION, "Invalid parametric curve type %d", Type); 724 return NULL; 725 } 726 727 memset(&Seg0, 0, sizeof(Seg0)); 728 729 Seg0.x0 = MINUS_INF; 730 Seg0.x1 = PLUS_INF; 731 Seg0.Type = Type; 732 733 size = c->ParameterCount[Pos] * sizeof(cmsFloat64Number); 734 memmove(Seg0.Params, Params, size); 735 736 return cmsBuildSegmentedToneCurve(ContextID, 1, &Seg0); 737 } 738 739 740 741 // Build a gamma table based on gamma constant 742 cmsToneCurve* CMSEXPORT cmsBuildGamma(cmsContext ContextID, cmsFloat64Number Gamma) 743 { 744 return cmsBuildParametricToneCurve(ContextID, 1, &Gamma); 745 } 746 747 748 // Free all memory taken by the gamma curve 749 void CMSEXPORT cmsFreeToneCurve(cmsToneCurve* Curve) 750 { 751 cmsContext ContextID; 752 753 // added by Xiaochuan Liu 754 // Curve->InterpParams may be null 755 if (Curve == NULL || Curve->InterpParams == NULL) return; 756 757 ContextID = Curve ->InterpParams->ContextID; 758 759 _cmsFreeInterpParams(Curve ->InterpParams); 760 Curve ->InterpParams = NULL; 761 762 if (Curve -> Table16) 763 { 764 _cmsFree(ContextID, Curve ->Table16); 765 Curve ->Table16 = NULL; 766 } 767 768 if (Curve ->Segments) { 769 770 cmsUInt32Number i; 771 772 for (i=0; i < Curve ->nSegments; i++) { 773 774 if (Curve ->Segments[i].SampledPoints) { 775 _cmsFree(ContextID, Curve ->Segments[i].SampledPoints); 776 Curve ->Segments[i].SampledPoints = NULL; 777 } 778 779 if (Curve ->SegInterp[i] != 0) 780 { 781 _cmsFreeInterpParams(Curve->SegInterp[i]); 782 Curve->SegInterp[i] = NULL; 783 } 784 } 785 786 _cmsFree(ContextID, Curve ->Segments); 787 Curve ->Segments = NULL; 788 _cmsFree(ContextID, Curve ->SegInterp); 789 Curve ->SegInterp = NULL; 790 } 791 792 if (Curve -> Evals) 793 { 794 _cmsFree(ContextID, Curve -> Evals); 795 Curve -> Evals = NULL; 796 } 797 798 if (Curve) 799 { 800 _cmsFree(ContextID, Curve); 801 Curve = NULL; 802 } 803 } 804 805 // Utility function, free 3 gamma tables 806 void CMSEXPORT cmsFreeToneCurveTriple(cmsToneCurve* Curve[3]) 807 { 808 809 _cmsAssert(Curve != NULL); 810 811 if (Curve[0] != NULL) cmsFreeToneCurve(Curve[0]); 812 if (Curve[1] != NULL) cmsFreeToneCurve(Curve[1]); 813 if (Curve[2] != NULL) cmsFreeToneCurve(Curve[2]); 814 815 Curve[0] = Curve[1] = Curve[2] = NULL; 816 } 817 818 819 // Duplicate a gamma table 820 cmsToneCurve* CMSEXPORT cmsDupToneCurve(const cmsToneCurve* In) 821 { 822 // Xiaochuan Liu 823 // fix openpdf bug(mantis id:0055683, google id:360198) 824 // the function CurveSetElemTypeFree in cmslut.c also needs to check pointer 825 if (In == NULL || In ->InterpParams == NULL) return NULL; 826 827 return AllocateToneCurveStruct(In ->InterpParams ->ContextID, In ->nEntries, In ->nSegments, In ->Segments, In ->Table16); 828 } 829 830 // Joins two curves for X and Y. Curves should be monotonic. 831 // We want to get 832 // 833 // y = Y^-1(X(t)) 834 // 835 cmsToneCurve* CMSEXPORT cmsJoinToneCurve(cmsContext ContextID, 836 const cmsToneCurve* X, 837 const cmsToneCurve* Y, cmsUInt32Number nResultingPoints) 838 { 839 cmsToneCurve* out = NULL; 840 cmsToneCurve* Yreversed = NULL; 841 cmsFloat32Number t, x; 842 cmsFloat32Number* Res = NULL; 843 cmsUInt32Number i; 844 845 846 _cmsAssert(X != NULL); 847 _cmsAssert(Y != NULL); 848 849 Yreversed = cmsReverseToneCurveEx(nResultingPoints, Y); 850 if (Yreversed == NULL) goto Error; 851 852 Res = (cmsFloat32Number*) _cmsCalloc(ContextID, nResultingPoints, sizeof(cmsFloat32Number)); 853 if (Res == NULL) goto Error; 854 855 //Iterate 856 for (i=0; i < nResultingPoints; i++) { 857 858 t = (cmsFloat32Number) i / (nResultingPoints-1); 859 x = cmsEvalToneCurveFloat(X, t); 860 Res[i] = cmsEvalToneCurveFloat(Yreversed, x); 861 } 862 863 // Allocate space for output 864 out = cmsBuildTabulatedToneCurveFloat(ContextID, nResultingPoints, Res); 865 866 Error: 867 868 if (Res != NULL) _cmsFree(ContextID, Res); 869 if (Yreversed != NULL) cmsFreeToneCurve(Yreversed); 870 871 return out; 872 } 873 874 875 876 // Get the surrounding nodes. This is tricky on non-monotonic tables 877 static 878 int GetInterval(cmsFloat64Number In, const cmsUInt16Number LutTable[], const struct _cms_interp_struc* p) 879 { 880 int i; 881 int y0, y1; 882 883 // A 1 point table is not allowed 884 if (p -> Domain[0] < 1) return -1; 885 886 // Let's see if ascending or descending. 887 if (LutTable[0] < LutTable[p ->Domain[0]]) { 888 889 // Table is overall ascending 890 for (i=p->Domain[0]-1; i >=0; --i) { 891 892 y0 = LutTable[i]; 893 y1 = LutTable[i+1]; 894 895 if (y0 <= y1) { // Increasing 896 if (In >= y0 && In <= y1) return i; 897 } 898 else 899 if (y1 < y0) { // Decreasing 900 if (In >= y1 && In <= y0) return i; 901 } 902 } 903 } 904 else { 905 // Table is overall descending 906 for (i=0; i < (int) p -> Domain[0]; i++) { 907 908 y0 = LutTable[i]; 909 y1 = LutTable[i+1]; 910 911 if (y0 <= y1) { // Increasing 912 if (In >= y0 && In <= y1) return i; 913 } 914 else 915 if (y1 < y0) { // Decreasing 916 if (In >= y1 && In <= y0) return i; 917 } 918 } 919 } 920 921 return -1; 922 } 923 924 // Reverse a gamma table 925 cmsToneCurve* CMSEXPORT cmsReverseToneCurveEx(cmsInt32Number nResultSamples, const cmsToneCurve* InCurve) 926 { 927 cmsToneCurve *out; 928 cmsFloat64Number a = 0, b = 0, y, x1, y1, x2, y2; 929 int i, j; 930 int Ascending; 931 932 _cmsAssert(InCurve != NULL); 933 934 // Try to reverse it analytically whatever possible 935 936 if (InCurve ->nSegments == 1 && InCurve ->Segments[0].Type > 0 && 937 /* InCurve -> Segments[0].Type <= 5 */ 938 GetParametricCurveByType(InCurve ->InterpParams->ContextID, InCurve ->Segments[0].Type, NULL) != NULL) { 939 940 return cmsBuildParametricToneCurve(InCurve ->InterpParams->ContextID, 941 -(InCurve -> Segments[0].Type), 942 InCurve -> Segments[0].Params); 943 } 944 945 // Nope, reverse the table. 946 out = cmsBuildTabulatedToneCurve16(InCurve ->InterpParams->ContextID, nResultSamples, NULL); 947 if (out == NULL) 948 return NULL; 949 950 // We want to know if this is an ascending or descending table 951 Ascending = !cmsIsToneCurveDescending(InCurve); 952 953 // Iterate across Y axis 954 for (i=0; i < nResultSamples; i++) { 955 956 y = (cmsFloat64Number) i * 65535.0 / (nResultSamples - 1); 957 958 // Find interval in which y is within. 959 j = GetInterval(y, InCurve->Table16, InCurve->InterpParams); 960 if (j >= 0) { 961 962 963 // Get limits of interval 964 x1 = InCurve ->Table16[j]; 965 x2 = InCurve ->Table16[j+1]; 966 967 y1 = (cmsFloat64Number) (j * 65535.0) / (InCurve ->nEntries - 1); 968 y2 = (cmsFloat64Number) ((j+1) * 65535.0 ) / (InCurve ->nEntries - 1); 969 970 // If collapsed, then use any 971 if (x1 == x2) { 972 973 out ->Table16[i] = _cmsQuickSaturateWord(Ascending ? y2 : y1); 974 continue; 975 976 } else { 977 978 // Interpolate 979 a = (y2 - y1) / (x2 - x1); 980 b = y2 - a * x2; 981 } 982 } 983 984 out ->Table16[i] = _cmsQuickSaturateWord(a* y + b); 985 } 986 987 988 return out; 989 } 990 991 // Reverse a gamma table 992 cmsToneCurve* CMSEXPORT cmsReverseToneCurve(const cmsToneCurve* InGamma) 993 { 994 _cmsAssert(InGamma != NULL); 995 996 return cmsReverseToneCurveEx(4096, InGamma); 997 } 998 999 // From: Eilers, P.H.C. (1994) Smoothing and interpolation with finite 1000 // differences. in: Graphic Gems IV, Heckbert, P.S. (ed.), Academic press. 1001 // 1002 // Smoothing and interpolation with second differences. 1003 // 1004 // Input: weights (w), data (y): vector from 1 to m. 1005 // Input: smoothing parameter (lambda), length (m). 1006 // Output: smoothed vector (z): vector from 1 to m. 1007 1008 static 1009 cmsBool smooth2(cmsContext ContextID, cmsFloat32Number w[], cmsFloat32Number y[], cmsFloat32Number z[], cmsFloat32Number lambda, int m) 1010 { 1011 int i, i1, i2; 1012 cmsFloat32Number *c, *d, *e; 1013 cmsBool st; 1014 1015 1016 c = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number)); 1017 d = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number)); 1018 e = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number)); 1019 1020 if (c != NULL && d != NULL && e != NULL) { 1021 1022 1023 d[1] = w[1] + lambda; 1024 c[1] = -2 * lambda / d[1]; 1025 e[1] = lambda /d[1]; 1026 z[1] = w[1] * y[1]; 1027 d[2] = w[2] + 5 * lambda - d[1] * c[1] * c[1]; 1028 c[2] = (-4 * lambda - d[1] * c[1] * e[1]) / d[2]; 1029 e[2] = lambda / d[2]; 1030 z[2] = w[2] * y[2] - c[1] * z[1]; 1031 1032 for (i = 3; i < m - 1; i++) { 1033 i1 = i - 1; i2 = i - 2; 1034 d[i]= w[i] + 6 * lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2]; 1035 c[i] = (-4 * lambda -d[i1] * c[i1] * e[i1])/ d[i]; 1036 e[i] = lambda / d[i]; 1037 z[i] = w[i] * y[i] - c[i1] * z[i1] - e[i2] * z[i2]; 1038 } 1039 1040 i1 = m - 2; i2 = m - 3; 1041 1042 d[m - 1] = w[m - 1] + 5 * lambda -c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2]; 1043 c[m - 1] = (-2 * lambda - d[i1] * c[i1] * e[i1]) / d[m - 1]; 1044 z[m - 1] = w[m - 1] * y[m - 1] - c[i1] * z[i1] - e[i2] * z[i2]; 1045 i1 = m - 1; i2 = m - 2; 1046 1047 d[m] = w[m] + lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2]; 1048 z[m] = (w[m] * y[m] - c[i1] * z[i1] - e[i2] * z[i2]) / d[m]; 1049 z[m - 1] = z[m - 1] / d[m - 1] - c[m - 1] * z[m]; 1050 1051 for (i = m - 2; 1<= i; i--) 1052 z[i] = z[i] / d[i] - c[i] * z[i + 1] - e[i] * z[i + 2]; 1053 1054 st = TRUE; 1055 } 1056 else st = FALSE; 1057 1058 if (c != NULL) _cmsFree(ContextID, c); 1059 if (d != NULL) _cmsFree(ContextID, d); 1060 if (e != NULL) _cmsFree(ContextID, e); 1061 1062 return st; 1063 } 1064 1065 // Smooths a curve sampled at regular intervals. 1066 cmsBool CMSEXPORT cmsSmoothToneCurve(cmsToneCurve* Tab, cmsFloat64Number lambda) 1067 { 1068 cmsFloat32Number w[MAX_NODES_IN_CURVE], y[MAX_NODES_IN_CURVE], z[MAX_NODES_IN_CURVE]; 1069 int i, nItems, Zeros, Poles; 1070 1071 if (Tab == NULL) return FALSE; 1072 1073 if (cmsIsToneCurveLinear(Tab)) return TRUE; // Nothing to do 1074 1075 nItems = Tab -> nEntries; 1076 1077 if (nItems >= MAX_NODES_IN_CURVE) { 1078 cmsSignalError(Tab ->InterpParams->ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: too many points."); 1079 return FALSE; 1080 } 1081 1082 memset(w, 0, nItems * sizeof(cmsFloat32Number)); 1083 memset(y, 0, nItems * sizeof(cmsFloat32Number)); 1084 memset(z, 0, nItems * sizeof(cmsFloat32Number)); 1085 1086 for (i=0; i < nItems; i++) 1087 { 1088 y[i+1] = (cmsFloat32Number) Tab -> Table16[i]; 1089 w[i+1] = 1.0; 1090 } 1091 1092 if (!smooth2(Tab ->InterpParams->ContextID, w, y, z, (cmsFloat32Number) lambda, nItems)) return FALSE; 1093 1094 // Do some reality - checking... 1095 Zeros = Poles = 0; 1096 for (i=nItems; i > 1; --i) { 1097 1098 if (z[i] == 0.) Zeros++; 1099 if (z[i] >= 65535.) Poles++; 1100 if (z[i] < z[i-1]) { 1101 cmsSignalError(Tab ->InterpParams->ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Non-Monotonic."); 1102 return FALSE; 1103 } 1104 } 1105 1106 if (Zeros > (nItems / 3)) { 1107 cmsSignalError(Tab ->InterpParams->ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly zeros."); 1108 return FALSE; 1109 } 1110 if (Poles > (nItems / 3)) { 1111 cmsSignalError(Tab ->InterpParams->ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly poles."); 1112 return FALSE; 1113 } 1114 1115 // Seems ok 1116 for (i=0; i < nItems; i++) { 1117 1118 // Clamp to cmsUInt16Number 1119 Tab -> Table16[i] = _cmsQuickSaturateWord(z[i+1]); 1120 } 1121 1122 return TRUE; 1123 } 1124 1125 // Is a table linear? Do not use parametric since we cannot guarantee some weird parameters resulting 1126 // in a linear table. This way assures it is linear in 12 bits, which should be enought in most cases. 1127 cmsBool CMSEXPORT cmsIsToneCurveLinear(const cmsToneCurve* Curve) 1128 { 1129 cmsUInt32Number i; 1130 int diff; 1131 1132 _cmsAssert(Curve != NULL); 1133 1134 for (i=0; i < Curve ->nEntries; i++) { 1135 1136 diff = abs((int) Curve->Table16[i] - (int) _cmsQuantizeVal(i, Curve ->nEntries)); 1137 if (diff > 0x0f) 1138 return FALSE; 1139 } 1140 1141 return TRUE; 1142 } 1143 1144 // Same, but for monotonicity 1145 cmsBool CMSEXPORT cmsIsToneCurveMonotonic(const cmsToneCurve* t) 1146 { 1147 int n; 1148 int i, last; 1149 cmsBool lDescending; 1150 1151 _cmsAssert(t != NULL); 1152 1153 // Degenerated curves are monotonic? Ok, let's pass them 1154 n = t ->nEntries; 1155 if (n < 2) return TRUE; 1156 1157 // Curve direction 1158 lDescending = cmsIsToneCurveDescending(t); 1159 1160 if (lDescending) { 1161 1162 last = t ->Table16[0]; 1163 1164 for (i = 1; i < n; i++) { 1165 1166 if (t ->Table16[i] - last > 2) // We allow some ripple 1167 return FALSE; 1168 else 1169 last = t ->Table16[i]; 1170 1171 } 1172 } 1173 else { 1174 1175 last = t ->Table16[n-1]; 1176 1177 for (i = n-2; i >= 0; --i) { 1178 1179 if (t ->Table16[i] - last > 2) 1180 return FALSE; 1181 else 1182 last = t ->Table16[i]; 1183 1184 } 1185 } 1186 1187 return TRUE; 1188 } 1189 1190 // Same, but for descending tables 1191 cmsBool CMSEXPORT cmsIsToneCurveDescending(const cmsToneCurve* t) 1192 { 1193 _cmsAssert(t != NULL); 1194 1195 return t ->Table16[0] > t ->Table16[t ->nEntries-1]; 1196 } 1197 1198 1199 // Another info fn: is out gamma table multisegment? 1200 cmsBool CMSEXPORT cmsIsToneCurveMultisegment(const cmsToneCurve* t) 1201 { 1202 _cmsAssert(t != NULL); 1203 1204 return t -> nSegments > 1; 1205 } 1206 1207 cmsInt32Number CMSEXPORT cmsGetToneCurveParametricType(const cmsToneCurve* t) 1208 { 1209 _cmsAssert(t != NULL); 1210 1211 if (t -> nSegments != 1) return 0; 1212 return t ->Segments[0].Type; 1213 } 1214 1215 // We need accuracy this time 1216 cmsFloat32Number CMSEXPORT cmsEvalToneCurveFloat(const cmsToneCurve* Curve, cmsFloat32Number v) 1217 { 1218 _cmsAssert(Curve != NULL); 1219 1220 // Check for 16 bits table. If so, this is a limited-precision tone curve 1221 if (Curve ->nSegments == 0) { 1222 1223 cmsUInt16Number In, Out; 1224 1225 In = (cmsUInt16Number) _cmsQuickSaturateWord(v * 65535.0); 1226 Out = cmsEvalToneCurve16(Curve, In); 1227 1228 return (cmsFloat32Number) (Out / 65535.0); 1229 } 1230 1231 return (cmsFloat32Number) EvalSegmentedFn(Curve, v); 1232 } 1233 1234 // We need xput over here 1235 cmsUInt16Number CMSEXPORT cmsEvalToneCurve16(const cmsToneCurve* Curve, cmsUInt16Number v) 1236 { 1237 cmsUInt16Number out; 1238 1239 _cmsAssert(Curve != NULL); 1240 1241 Curve ->InterpParams ->Interpolation.Lerp16(&v, &out, Curve ->InterpParams); 1242 return out; 1243 } 1244 1245 1246 // Least squares fitting. 1247 // A mathematical procedure for finding the best-fitting curve to a given set of points by 1248 // minimizing the sum of the squares of the offsets ("the residuals") of the points from the curve. 1249 // The sum of the squares of the offsets is used instead of the offset absolute values because 1250 // this allows the residuals to be treated as a continuous differentiable quantity. 1251 // 1252 // y = f(x) = x ^ g 1253 // 1254 // R = (yi - (xi^g)) 1255 // R2 = (yi - (xi^g))2 1256 // SUM R2 = SUM (yi - (xi^g))2 1257 // 1258 // dR2/dg = -2 SUM x^g log(x)(y - x^g) 1259 // solving for dR2/dg = 0 1260 // 1261 // g = 1/n * SUM(log(y) / log(x)) 1262 1263 cmsFloat64Number CMSEXPORT cmsEstimateGamma(const cmsToneCurve* t, cmsFloat64Number Precision) 1264 { 1265 cmsFloat64Number gamma, sum, sum2; 1266 cmsFloat64Number n, x, y, Std; 1267 cmsUInt32Number i; 1268 1269 _cmsAssert(t != NULL); 1270 1271 sum = sum2 = n = 0; 1272 1273 // Excluding endpoints 1274 for (i=1; i < (MAX_NODES_IN_CURVE-1); i++) { 1275 1276 x = (cmsFloat64Number) i / (MAX_NODES_IN_CURVE-1); 1277 y = (cmsFloat64Number) cmsEvalToneCurveFloat(t, (cmsFloat32Number) x); 1278 1279 // Avoid 7% on lower part to prevent 1280 // artifacts due to linear ramps 1281 1282 if (y > 0. && y < 1. && x > 0.07) { 1283 1284 gamma = log(y) / log(x); 1285 sum += gamma; 1286 sum2 += gamma * gamma; 1287 n++; 1288 } 1289 } 1290 1291 // Take a look on SD to see if gamma isn't exponential at all 1292 Std = sqrt((n * sum2 - sum * sum) / (n*(n-1))); 1293 1294 if (Std > Precision) 1295 return -1.0; 1296 1297 return (sum / n); // The mean 1298 } 1299
