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| 1 #include <cmath> | |
| 2 | |
| 3 #include "SkBitmap.h" | |
| 4 #include "skpdiff_util.h" | |
| 5 #include "SkPMetric.h" | |
| 6 #include "SkPMetricUtil_generated.h" | |
| 7 | |
| 8 struct RGB { | |
| 9 float r, g, b; | |
| 10 }; | |
| 11 | |
| 12 struct LAB { | |
| 13 float l, a, b; | |
| 14 }; | |
| 15 | |
| 16 template<class T> | |
| 17 struct Image2D { | |
| 18 int width; | |
| 19 int height; | |
| 20 T* image; | |
| 21 | |
| 22 Image2D(int w, int h) | |
| 23 : width(w), | |
| 24 height(h) { | |
| 25 SkASSERT(w > 0); | |
| 26 SkASSERT(h > 0); | |
| 27 image = SkNEW_ARRAY(T, w * h); | |
| 28 } | |
| 29 | |
| 30 ~Image2D() { | |
| 31 SkDELETE_ARRAY(image); | |
| 32 } | |
| 33 | |
| 34 void readPixel(int x, int y, T* pixel) const { | |
| 35 SkASSERT(x >= 0); | |
| 36 SkASSERT(y >= 0); | |
| 37 SkASSERT(x < width); | |
| 38 SkASSERT(y < height); | |
| 39 *pixel = image[y * width + x]; | |
| 40 } | |
| 41 | |
| 42 T* getRow(int y) const { | |
| 43 return &image[y * width]; | |
| 44 } | |
| 45 | |
| 46 void writePixel(int x, int y, const T& pixel) { | |
| 47 SkASSERT(x >= 0); | |
| 48 SkASSERT(y >= 0); | |
| 49 SkASSERT(x < width); | |
| 50 SkASSERT(y < height); | |
| 51 image[y * width + x] = pixel; | |
| 52 } | |
| 53 }; | |
| 54 | |
| 55 typedef Image2D<float> ImageL; | |
| 56 typedef Image2D<RGB> ImageRGB; | |
| 57 typedef Image2D<LAB> ImageLAB; | |
| 58 | |
| 59 template<class T> | |
| 60 struct ImageArray | |
| 61 { | |
| 62 int slices; | |
| 63 Image2D<T>** image; | |
| 64 | |
| 65 ImageArray(int w, int h, int s) | |
| 66 : slices(s) { | |
| 67 SkASSERT(s > 0); | |
| 68 image = SkNEW_ARRAY(Image2D<T>*, s); | |
| 69 for (int sliceIndex = 0; sliceIndex < slices; sliceIndex++) { | |
| 70 image[sliceIndex] = SkNEW_ARGS(Image2D<T>, (w, h)); | |
| 71 } | |
| 72 } | |
| 73 | |
| 74 ~ImageArray() { | |
| 75 for (int sliceIndex = 0; sliceIndex < slices; sliceIndex++) { | |
| 76 SkDELETE(image[sliceIndex]); | |
| 77 } | |
| 78 SkDELETE_ARRAY(image); | |
| 79 } | |
| 80 | |
| 81 Image2D<T>* getLayer(int z) const { | |
| 82 SkASSERT(z >= 0); | |
| 83 SkASSERT(z < slices); | |
| 84 return image[z]; | |
| 85 } | |
| 86 }; | |
| 87 | |
| 88 typedef ImageArray<float> ImageL3D; | |
| 89 | |
| 90 | |
| 91 #define MAT_ROW_MULT(rc,gc,bc) r*rc + g*gc + b*bc | |
| 92 | |
| 93 static void adobergb_to_cielab(float r, float g, float b, LAB* lab) { | |
| 94 // Conversion of Adobe RGB to XYZ taken from from "Adobe RGB (1998) ColorIma
ge Encoding" | |
| 95 // URL:http://www.adobe.com/digitalimag/pdfs/AdobeRGB1998.pdf | |
| 96 // Section: 4.3.5.3 | |
| 97 // See Also: http://en.wikipedia.org/wiki/Adobe_rgb | |
| 98 float x = MAT_ROW_MULT(0.57667f, 0.18556f, 0.18823f); | |
| 99 float y = MAT_ROW_MULT(0.29734f, 0.62736f, 0.07529f); | |
| 100 float z = MAT_ROW_MULT(0.02703f, 0.07069f, 0.99134f); | |
| 101 | |
| 102 // The following is the white point in XYZ, so it's simply the row wise addi
tion of the above | |
| 103 // matrix. | |
| 104 const float xw = 0.5767f + 0.185556f + 0.188212f; | |
| 105 const float yw = 0.297361f + 0.627355f + 0.0752847f; | |
| 106 const float zw = 0.0270328f + 0.0706879f + 0.991248f; | |
| 107 | |
| 108 // This is the XYZ color point relative to the white point | |
| 109 float f[3] = { x / xw, y / yw, z / zw }; | |
| 110 | |
| 111 // Conversion from XYZ to LAB taken from | |
| 112 // http://en.wikipedia.org/wiki/CIELAB#Forward_transformation | |
| 113 for (int i = 0; i < 3; i++) { | |
| 114 if (f[i] >= 0.008856f) { | |
| 115 f[i] = SkPMetricUtil::get_cube_root(f[i]); | |
| 116 } else { | |
| 117 f[i] = 7.787f * f[i] + 4.0f / 29.0f; | |
| 118 } | |
| 119 } | |
| 120 lab->l = 116.0f * f[1] - 16.0f; | |
| 121 lab->a = 500.0f * (f[0] - f[1]); | |
| 122 lab->b = 200.0f * (f[1] - f[2]); | |
| 123 } | |
| 124 | |
| 125 /// Converts a 8888 bitmap to LAB color space and puts it into the output | |
| 126 static void bitmap_to_cielab(const SkBitmap* bitmap, ImageLAB* outImageLAB) { | |
| 127 SkASSERT(bitmap->config() == SkBitmap::kARGB_8888_Config); | |
| 128 | |
| 129 int width = bitmap->width(); | |
| 130 int height = bitmap->height(); | |
| 131 SkASSERT(outImageLAB->width == width); | |
| 132 SkASSERT(outImageLAB->height == height); | |
| 133 | |
| 134 bitmap->lockPixels(); | |
| 135 RGB rgb; | |
| 136 LAB lab; | |
| 137 for (int y = 0; y < height; y++) { | |
| 138 unsigned char* row = (unsigned char*)bitmap->getAddr(0, y); | |
| 139 for (int x = 0; x < width; x++) { | |
| 140 // Perform gamma correction which is assumed to be 2.2 | |
| 141 rgb.r = SkPMetricUtil::get_gamma(row[x * 4 + 2]); | |
| 142 rgb.g = SkPMetricUtil::get_gamma(row[x * 4 + 1]); | |
| 143 rgb.b = SkPMetricUtil::get_gamma(row[x * 4 + 0]); | |
| 144 adobergb_to_cielab(rgb.r, rgb.g, rgb.b, &lab); | |
| 145 outImageLAB->writePixel(x, y, lab); | |
| 146 } | |
| 147 } | |
| 148 bitmap->unlockPixels(); | |
| 149 } | |
| 150 | |
| 151 // From Barten SPIE 1989 | |
| 152 static float contrast_sensitivity(float cyclesPerDegree, float luminance) { | |
| 153 float a = 440.0f * powf(1.0f + 0.7f / luminance, -0.2f); | |
| 154 float b = 0.3f * powf(1.0f + 100.0f / luminance, 0.15f); | |
| 155 return a * | |
| 156 cyclesPerDegree * | |
| 157 expf(-b * cyclesPerDegree) * | |
| 158 sqrtf(1.0f + 0.06f * expf(b * cyclesPerDegree)); | |
| 159 } | |
| 160 | |
| 161 #if 0 | |
| 162 // We're keeping these around for reference and in case the lookup tables are no
longer desired. | |
| 163 // They are no longer called by any code in this file. | |
| 164 | |
| 165 // From Daly 1993 | |
| 166 static float visual_mask(float contrast) { | |
| 167 float x = powf(392.498f * contrast, 0.7f); | |
| 168 x = powf(0.0153f * x, 4.0f); | |
| 169 return powf(1.0f + x, 0.25f); | |
| 170 } | |
| 171 | |
| 172 // From Ward Larson Siggraph 1997 | |
| 173 static float threshold_vs_intensity(float adaptationLuminance) { | |
| 174 float logLum = log10f(adaptationLuminance); | |
| 175 float x; | |
| 176 if (logLum < -3.94f) { | |
| 177 x = -2.86f; | |
| 178 } else if (logLum < -1.44f) { | |
| 179 x = powf(0.405f * logLum + 1.6f, 2.18) - 2.86f; | |
| 180 } else if (logLum < -0.0184f) { | |
| 181 x = logLum - 0.395f; | |
| 182 } else if (logLum < 1.9f) { | |
| 183 x = powf(0.249f * logLum + 0.65f, 2.7f) - 0.72f; | |
| 184 } else { | |
| 185 x = logLum - 1.255f; | |
| 186 } | |
| 187 return powf(10.0f, x); | |
| 188 } | |
| 189 | |
| 190 #endif | |
| 191 | |
| 192 /// Simply takes the L channel from the input and puts it into the output | |
| 193 static void lab_to_l(const ImageLAB* imageLAB, ImageL* outImageL) { | |
| 194 for (int y = 0; y < imageLAB->height; y++) { | |
| 195 for (int x = 0; x < imageLAB->width; x++) { | |
| 196 LAB lab; | |
| 197 imageLAB->readPixel(x, y, &lab); | |
| 198 outImageL->writePixel(x, y, lab.l); | |
| 199 } | |
| 200 } | |
| 201 } | |
| 202 | |
| 203 /// Convolves an image with the given filter in one direction and saves it to th
e output image | |
| 204 static void convolve(const ImageL* imageL, bool vertical, ImageL* outImageL) { | |
| 205 SkASSERT(imageL->width == outImageL->width); | |
| 206 SkASSERT(imageL->height == outImageL->height); | |
| 207 | |
| 208 const float matrix[] = { 0.05f, 0.25f, 0.4f, 0.25f, 0.05f }; | |
| 209 const int matrixCount = sizeof(matrix) / sizeof(float); | |
| 210 const int radius = matrixCount / 2; | |
| 211 | |
| 212 // Keep track of what rows are being operated on for quick access. | |
| 213 float* rowPtrs[matrixCount]; // Because matrixCount is constant, this won't
create a VLA | |
| 214 for (int y = radius; y < matrixCount; y++) { | |
| 215 rowPtrs[y] = imageL->getRow(y - radius); | |
| 216 } | |
| 217 float* writeRow = outImageL->getRow(0); | |
| 218 | |
| 219 for (int y = 0; y < imageL->height; y++) { | |
| 220 for (int x = 0; x < imageL->width; x++) { | |
| 221 float lSum = 0.0f; | |
| 222 for (int xx = -radius; xx <= radius; xx++) { | |
| 223 int nx = x; | |
| 224 int ny = y; | |
| 225 | |
| 226 // We mirror at edges so that edge pixels that the filter weight
ing still makes | |
| 227 // sense. | |
| 228 if (vertical) { | |
| 229 ny += xx; | |
| 230 if (ny < 0) { | |
| 231 ny = -ny; | |
| 232 } | |
| 233 if (ny >= imageL->height) { | |
| 234 ny = imageL->height + (imageL->height - ny - 1); | |
| 235 } | |
| 236 } else { | |
| 237 nx += xx; | |
| 238 if (nx < 0) { | |
| 239 nx = -nx; | |
| 240 } | |
| 241 if (nx >= imageL->width) { | |
| 242 nx = imageL->width + (imageL->width - nx - 1); | |
| 243 } | |
| 244 } | |
| 245 | |
| 246 float weight = matrix[xx + radius]; | |
| 247 lSum += rowPtrs[ny - y + radius][nx] * weight; | |
| 248 } | |
| 249 writeRow[x] = lSum; | |
| 250 } | |
| 251 // As we move down, scroll the row pointers down with us | |
| 252 for (int y = 0; y < matrixCount - 1; y++) | |
| 253 { | |
| 254 rowPtrs[y] = rowPtrs[y + 1]; | |
| 255 } | |
| 256 rowPtrs[matrixCount - 1] += imageL->width; | |
| 257 writeRow += imageL->width; | |
| 258 } | |
| 259 } | |
| 260 | |
| 261 static double pmetric(const ImageLAB* baselineLAB, const ImageLAB* testLAB, SkTD
Array<SkIPoint>* poi) { | |
| 262 int width = baselineLAB->width; | |
| 263 int height = baselineLAB->height; | |
| 264 int maxLevels = 0; | |
| 265 | |
| 266 // Calculates how many levels to make by how many times the image can be div
ided in two | |
| 267 int smallerDimension = width < height ? width : height; | |
| 268 for ( ; smallerDimension > 1; smallerDimension /= 2) { | |
| 269 maxLevels++; | |
| 270 } | |
| 271 | |
| 272 const float fov = SK_ScalarPI / 180.0f * 45.0f; | |
| 273 float contrastSensitivityMax = contrast_sensitivity(3.248f, 100.0f); | |
| 274 float pixelsPerDegree = width / (2.0f * tanf(fov * 0.5f) * 180.0f / SK_Scala
rPI); | |
| 275 | |
| 276 ImageL3D baselineL(width, height, maxLevels); | |
| 277 ImageL3D testL(width, height, maxLevels); | |
| 278 ImageL scratchImageL(width, height); | |
| 279 float* cyclesPerDegree = SkNEW_ARRAY(float, maxLevels); | |
| 280 float* thresholdFactorFrequency = SkNEW_ARRAY(float, maxLevels - 2); | |
| 281 float* contrast = SkNEW_ARRAY(float, maxLevels - 2); | |
| 282 | |
| 283 lab_to_l(baselineLAB, baselineL.getLayer(0)); | |
| 284 lab_to_l(testLAB, testL.getLayer(0)); | |
| 285 | |
| 286 // Compute cpd - Cycles per degree on the pyramid | |
| 287 cyclesPerDegree[0] = 0.5f * pixelsPerDegree; | |
| 288 for (int levelIndex = 1; levelIndex < maxLevels; levelIndex++) { | |
| 289 cyclesPerDegree[levelIndex] = cyclesPerDegree[levelIndex - 1] * 0.5f; | |
| 290 } | |
| 291 | |
| 292 // Contrast sensitivity is based on image dimensions. Therefore it cannot be
statically | |
| 293 // generated. | |
| 294 float* contrastSensitivityTable = SkNEW_ARRAY(float, maxLevels * 1000); | |
| 295 for (int levelIndex = 0; levelIndex < maxLevels; levelIndex++) { | |
| 296 for (int csLum = 0; csLum < 1000; csLum++) { | |
| 297 contrastSensitivityTable[levelIndex * 1000 + csLum] = | |
| 298 contrast_sensitivity(cyclesPerDegree[levelIndex], (float)csLum / 10.0
f + 1e-5f); | |
| 299 } | |
| 300 } | |
| 301 | |
| 302 // Compute G - The convolved lum for the baseline | |
| 303 for (int levelIndex = 1; levelIndex < maxLevels; levelIndex++) { | |
| 304 convolve(baselineL.getLayer(levelIndex - 1), false, &scratchImageL); | |
| 305 convolve(&scratchImageL, true, baselineL.getLayer(levelIndex)); | |
| 306 } | |
| 307 for (int levelIndex = 1; levelIndex < maxLevels; levelIndex++) { | |
| 308 convolve(testL.getLayer(levelIndex - 1), false, &scratchImageL); | |
| 309 convolve(&scratchImageL, true, testL.getLayer(levelIndex)); | |
| 310 } | |
| 311 | |
| 312 // Compute F_freq - The elevation f | |
| 313 for (int levelIndex = 0; levelIndex < maxLevels - 2; levelIndex++) { | |
| 314 float cpd = cyclesPerDegree[levelIndex]; | |
| 315 thresholdFactorFrequency[levelIndex] = contrastSensitivityMax / | |
| 316 contrast_sensitivity(cpd, 100.0f)
; | |
| 317 } | |
| 318 | |
| 319 int failures = 0; | |
| 320 // Calculate F | |
| 321 for (int y = 0; y < height; y++) { | |
| 322 for (int x = 0; x < width; x++) { | |
| 323 float lBaseline; | |
| 324 float lTest; | |
| 325 baselineL.getLayer(0)->readPixel(x, y, &lBaseline); | |
| 326 testL.getLayer(0)->readPixel(x, y, &lTest); | |
| 327 | |
| 328 float avgLBaseline; | |
| 329 float avgLTest; | |
| 330 baselineL.getLayer(maxLevels - 1)->readPixel(x, y, &avgLBaseline); | |
| 331 testL.getLayer(maxLevels - 1)->readPixel(x, y, &avgLTest); | |
| 332 | |
| 333 float lAdapt = 0.5f * (avgLBaseline + avgLTest); | |
| 334 if (lAdapt < 1e-5f) { | |
| 335 lAdapt = 1e-5f; | |
| 336 } | |
| 337 | |
| 338 float contrastSum = 0.0f; | |
| 339 for (int levelIndex = 0; levelIndex < maxLevels - 2; levelIndex++) { | |
| 340 float baselineL0, baselineL1, baselineL2; | |
| 341 float testL0, testL1, testL2; | |
| 342 baselineL.getLayer(levelIndex + 0)->readPixel(x, y, &baselineL0)
; | |
| 343 testL. getLayer(levelIndex + 0)->readPixel(x, y, &testL0); | |
| 344 baselineL.getLayer(levelIndex + 1)->readPixel(x, y, &baselineL1)
; | |
| 345 testL. getLayer(levelIndex + 1)->readPixel(x, y, &testL1); | |
| 346 baselineL.getLayer(levelIndex + 2)->readPixel(x, y, &baselineL2)
; | |
| 347 testL. getLayer(levelIndex + 2)->readPixel(x, y, &testL2); | |
| 348 | |
| 349 float baselineContrast1 = fabsf(baselineL0 - baselineL1); | |
| 350 float testContrast1 = fabsf(testL0 - testL1); | |
| 351 float numerator = (baselineContrast1 > testContrast1) ? | |
| 352 baselineContrast1 : testContrast1; | |
| 353 | |
| 354 float baselineContrast2 = fabsf(baselineL2); | |
| 355 float testContrast2 = fabsf(testL2); | |
| 356 float denominator = (baselineContrast2 > testContrast2) ? | |
| 357 baselineContrast2 : testContrast2; | |
| 358 | |
| 359 // Avoid divides by close to zero | |
| 360 if (denominator < 1e-5f) { | |
| 361 denominator = 1e-5f; | |
| 362 } | |
| 363 contrast[levelIndex] = numerator / denominator; | |
| 364 contrastSum += contrast[levelIndex]; | |
| 365 } | |
| 366 | |
| 367 if (contrastSum < 1e-5f) { | |
| 368 contrastSum = 1e-5f; | |
| 369 } | |
| 370 | |
| 371 float F = 0.0f; | |
| 372 for (int levelIndex = 0; levelIndex < maxLevels - 2; levelIndex++) { | |
| 373 float contrastSensitivity = contrastSensitivityTable[levelIndex
* 1000 + | |
| 374 (int)(lAdap
t * 10.0)]; | |
| 375 float mask = SkPMetricUtil::get_visual_mask(contrast[levelIndex]
* | |
| 376 contrastSensitivity)
; | |
| 377 | |
| 378 F += contrast[levelIndex] + | |
| 379 thresholdFactorFrequency[levelIndex] * mask / contrastSum; | |
| 380 } | |
| 381 | |
| 382 if (F < 1.0f) { | |
| 383 F = 1.0f; | |
| 384 } | |
| 385 | |
| 386 if (F > 10.0f) { | |
| 387 F = 10.0f; | |
| 388 } | |
| 389 | |
| 390 | |
| 391 bool isFailure = false; | |
| 392 if (fabsf(lBaseline - lTest) > F * SkPMetricUtil::get_threshold_vs_i
ntensity(lAdapt)) { | |
| 393 isFailure = true; | |
| 394 } else { | |
| 395 LAB baselineColor; | |
| 396 LAB testColor; | |
| 397 baselineLAB->readPixel(x, y, &baselineColor); | |
| 398 testLAB->readPixel(x, y, &testColor); | |
| 399 float contrastA = baselineColor.a - testColor.a; | |
| 400 float contrastB = baselineColor.b - testColor.b; | |
| 401 float colorScale = 1.0f; | |
| 402 if (lAdapt < 10.0f) { | |
| 403 colorScale = lAdapt / 10.0f; | |
| 404 } | |
| 405 colorScale *= colorScale; | |
| 406 | |
| 407 if ((contrastA * contrastA + contrastB * contrastB) * colorScale
> F) | |
| 408 { | |
| 409 isFailure = true; | |
| 410 } | |
| 411 } | |
| 412 | |
| 413 if (isFailure) { | |
| 414 failures++; | |
| 415 poi->push()->set(x, y); | |
| 416 } | |
| 417 } | |
| 418 } | |
| 419 | |
| 420 SkDELETE_ARRAY(cyclesPerDegree); | |
| 421 SkDELETE_ARRAY(contrast); | |
| 422 SkDELETE_ARRAY(thresholdFactorFrequency); | |
| 423 SkDELETE_ARRAY(contrastSensitivityTable); | |
| 424 return 1.0 - (double)failures / (width * height); | |
| 425 } | |
| 426 | |
| 427 const char* SkPMetric::getName() { | |
| 428 return "perceptual"; | |
| 429 } | |
| 430 | |
| 431 int SkPMetric::queueDiff(SkBitmap* baseline, SkBitmap* test) { | |
| 432 double startTime = get_seconds(); | |
| 433 int diffID = fQueuedDiffs.count(); | |
| 434 QueuedDiff& diff = fQueuedDiffs.push_back(); | |
| 435 diff.result = 0.0; | |
| 436 | |
| 437 // Ensure the images are comparable | |
| 438 if (baseline->width() != test->width() || baseline->height() != test->height
() || | |
| 439 baseline->width() <= 0 || baseline->height() <= 0) { | |
| 440 diff.finished = true; | |
| 441 return diffID; | |
| 442 } | |
| 443 | |
| 444 ImageLAB baselineLAB(baseline->width(), baseline->height()); | |
| 445 ImageLAB testLAB(baseline->width(), baseline->height()); | |
| 446 | |
| 447 bitmap_to_cielab(baseline, &baselineLAB); | |
| 448 bitmap_to_cielab(test, &testLAB); | |
| 449 | |
| 450 diff.result = pmetric(&baselineLAB, &testLAB, &diff.poi); | |
| 451 | |
| 452 SkDebugf("Time: %f\n", (get_seconds() - startTime)); | |
| 453 | |
| 454 return diffID; | |
| 455 } | |
| 456 | |
| 457 | |
| 458 void SkPMetric::deleteDiff(int id) { | |
| 459 | |
| 460 } | |
| 461 | |
| 462 bool SkPMetric::isFinished(int id) { | |
| 463 return fQueuedDiffs[id].finished; | |
| 464 } | |
| 465 | |
| 466 double SkPMetric::getResult(int id) { | |
| 467 return fQueuedDiffs[id].result; | |
| 468 } | |
| 469 | |
| 470 int SkPMetric::getPointsOfInterestCount(int id) { | |
| 471 return fQueuedDiffs[id].poi.count(); | |
| 472 } | |
| 473 | |
| 474 SkIPoint* SkPMetric::getPointsOfInterest(int id) { | |
| 475 return fQueuedDiffs[id].poi.begin(); | |
| 476 } | |
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