#include <cmath>
#include <math.h>
#include "SkBitmap.h"
#include "skpdiff_util.h"
#include "SkPMetric.h"
#include "SkPMetricUtil_generated.h"
struct RGB {
float r, g, b;
};
struct LAB {
float l, a, b;
};
template<class T>
struct Image2D {
int width;
int height;
T* image;
Image2D(int w, int h)
: width(w),
height(h) {
SkASSERT(w > 0);
SkASSERT(h > 0);
image = SkNEW_ARRAY(T, w * h);
}
~Image2D() {
SkDELETE_ARRAY(image);
}
void readPixel(int x, int y, T* pixel) const {
SkASSERT(x >= 0);
SkASSERT(y >= 0);
SkASSERT(x < width);
SkASSERT(y < height);
*pixel = image[y * width + x];
}
T* getRow(int y) const {
return &image[y * width];
}
void writePixel(int x, int y, const T& pixel) {
SkASSERT(x >= 0);
SkASSERT(y >= 0);
SkASSERT(x < width);
SkASSERT(y < height);
image[y * width + x] = pixel;
}
};
typedef Image2D<float> ImageL;
typedef Image2D<RGB> ImageRGB;
typedef Image2D<LAB> ImageLAB;
template<class T>
struct ImageArray
{
int slices;
Image2D<T>** image;
ImageArray(int w, int h, int s)
: slices(s) {
SkASSERT(s > 0);
image = SkNEW_ARRAY(Image2D<T>*, s);
for (int sliceIndex = 0; sliceIndex < slices; sliceIndex++) {
image[sliceIndex] = SkNEW_ARGS(Image2D<T>, (w, h));
}
}
~ImageArray() {
for (int sliceIndex = 0; sliceIndex < slices; sliceIndex++) {
SkDELETE(image[sliceIndex]);
}
SkDELETE_ARRAY(image);
}
Image2D<T>* getLayer(int z) const {
SkASSERT(z >= 0);
SkASSERT(z < slices);
return image[z];
}
};
typedef ImageArray<float> ImageL3D;
#define MAT_ROW_MULT(rc,gc,bc) r*rc + g*gc + b*bc
static void adobergb_to_cielab(float r, float g, float b, LAB* lab) {
// Conversion of Adobe RGB to XYZ taken from from "Adobe RGB (1998) ColorImage Encoding"
// URL:http://www.adobe.com/digitalimag/pdfs/AdobeRGB1998.pdf
// Section: 4.3.5.3
// See Also: http://en.wikipedia.org/wiki/Adobe_rgb
float x = MAT_ROW_MULT(0.57667f, 0.18556f, 0.18823f);
float y = MAT_ROW_MULT(0.29734f, 0.62736f, 0.07529f);
float z = MAT_ROW_MULT(0.02703f, 0.07069f, 0.99134f);
// The following is the white point in XYZ, so it's simply the row wise addition of the above
// matrix.
const float xw = 0.5767f + 0.185556f + 0.188212f;
const float yw = 0.297361f + 0.627355f + 0.0752847f;
const float zw = 0.0270328f + 0.0706879f + 0.991248f;
// This is the XYZ color point relative to the white point
float f[3] = { x / xw, y / yw, z / zw };
// Conversion from XYZ to LAB taken from
// http://en.wikipedia.org/wiki/CIELAB#Forward_transformation
for (int i = 0; i < 3; i++) {
if (f[i] >= 0.008856f) {
f[i] = SkPMetricUtil::get_cube_root(f[i]);
} else {
f[i] = 7.787f * f[i] + 4.0f / 29.0f;
}
}
lab->l = 116.0f * f[1] - 16.0f;
lab->a = 500.0f * (f[0] - f[1]);
lab->b = 200.0f * (f[1] - f[2]);
}
/// Converts a 8888 bitmap to LAB color space and puts it into the output
static bool bitmap_to_cielab(const SkBitmap* bitmap, ImageLAB* outImageLAB) {
SkBitmap bm8888;
if (bitmap->colorType() != kN32_SkColorType) {
if (!bitmap->copyTo(&bm8888, kN32_SkColorType)) {
return false;
}
bitmap = &bm8888;
}
int width = bitmap->width();
int height = bitmap->height();
SkASSERT(outImageLAB->width == width);
SkASSERT(outImageLAB->height == height);
bitmap->lockPixels();
RGB rgb;
LAB lab;
for (int y = 0; y < height; y++) {
unsigned char* row = (unsigned char*)bitmap->getAddr(0, y);
for (int x = 0; x < width; x++) {
// Perform gamma correction which is assumed to be 2.2
rgb.r = SkPMetricUtil::get_gamma(row[x * 4 + 2]);
rgb.g = SkPMetricUtil::get_gamma(row[x * 4 + 1]);
rgb.b = SkPMetricUtil::get_gamma(row[x * 4 + 0]);
adobergb_to_cielab(rgb.r, rgb.g, rgb.b, &lab);
outImageLAB->writePixel(x, y, lab);
}
}
bitmap->unlockPixels();
return true;
}
// From Barten SPIE 1989
static float contrast_sensitivity(float cyclesPerDegree, float luminance) {
float a = 440.0f * powf(1.0f + 0.7f / luminance, -0.2f);
float b = 0.3f * powf(1.0f + 100.0f / luminance, 0.15f);
float exp = expf(-b * cyclesPerDegree);
float root = sqrtf(1.0f + 0.06f * expf(b * cyclesPerDegree));
if (!SkScalarIsFinite(exp) || !SkScalarIsFinite(root)) {
return 0;
}
return a * cyclesPerDegree * exp * root;
}
#if 0
// We're keeping these around for reference and in case the lookup tables are no longer desired.
// They are no longer called by any code in this file.
// From Daly 1993
static float visual_mask(float contrast) {
float x = powf(392.498f * contrast, 0.7f);
x = powf(0.0153f * x, 4.0f);
return powf(1.0f + x, 0.25f);
}
// From Ward Larson Siggraph 1997
static float threshold_vs_intensity(float adaptationLuminance) {
float logLum = log10f(adaptationLuminance);
float x;
if (logLum < -3.94f) {
x = -2.86f;
} else if (logLum < -1.44f) {
x = powf(0.405f * logLum + 1.6f, 2.18) - 2.86f;
} else if (logLum < -0.0184f) {
x = logLum - 0.395f;
} else if (logLum < 1.9f) {
x = powf(0.249f * logLum + 0.65f, 2.7f) - 0.72f;
} else {
x = logLum - 1.255f;
}
return powf(10.0f, x);
}
#endif
/// Simply takes the L channel from the input and puts it into the output
static void lab_to_l(const ImageLAB* imageLAB, ImageL* outImageL) {
for (int y = 0; y < imageLAB->height; y++) {
for (int x = 0; x < imageLAB->width; x++) {
LAB lab;
imageLAB->readPixel(x, y, &lab);
outImageL->writePixel(x, y, lab.l);
}
}
}
/// Convolves an image with the given filter in one direction and saves it to the output image
static void convolve(const ImageL* imageL, bool vertical, ImageL* outImageL) {
SkASSERT(imageL->width == outImageL->width);
SkASSERT(imageL->height == outImageL->height);
const float matrix[] = { 0.05f, 0.25f, 0.4f, 0.25f, 0.05f };
const int matrixCount = sizeof(matrix) / sizeof(float);
const int radius = matrixCount / 2;
// Keep track of what rows are being operated on for quick access.
float* rowPtrs[matrixCount]; // Because matrixCount is constant, this won't create a VLA
for (int y = radius; y < matrixCount; y++) {
rowPtrs[y] = imageL->getRow(y - radius);
}
float* writeRow = outImageL->getRow(0);
for (int y = 0; y < imageL->height; y++) {
for (int x = 0; x < imageL->width; x++) {
float lSum = 0.0f;
for (int xx = -radius; xx <= radius; xx++) {
int nx = x;
int ny = y;
// We mirror at edges so that edge pixels that the filter weighting still makes
// sense.
if (vertical) {
ny += xx;
if (ny < 0) {
ny = -ny;
}
if (ny >= imageL->height) {
ny = imageL->height + (imageL->height - ny - 1);
}
} else {
nx += xx;
if (nx < 0) {
nx = -nx;
}
if (nx >= imageL->width) {
nx = imageL->width + (imageL->width - nx - 1);
}
}
float weight = matrix[xx + radius];
lSum += rowPtrs[ny - y + radius][nx] * weight;
}
writeRow[x] = lSum;
}
// As we move down, scroll the row pointers down with us
for (int y = 0; y < matrixCount - 1; y++)
{
rowPtrs[y] = rowPtrs[y + 1];
}
rowPtrs[matrixCount - 1] += imageL->width;
writeRow += imageL->width;
}
}
static double pmetric(const ImageLAB* baselineLAB, const ImageLAB* testLAB, int* poiCount) {
SkASSERT(baselineLAB);
SkASSERT(testLAB);
SkASSERT(poiCount);
int width = baselineLAB->width;
int height = baselineLAB->height;
int maxLevels = 0;
// Calculates how many levels to make by how many times the image can be divided in two
int smallerDimension = width < height ? width : height;
for ( ; smallerDimension > 1; smallerDimension /= 2) {
maxLevels++;
}
// We'll be creating new arrays with maxLevels - 2, and ImageL3D requires maxLevels > 0,
// so just return failure if we're less than 3.
if (maxLevels <= 2) {
return 0.0;
}
const float fov = SK_ScalarPI / 180.0f * 45.0f;
float contrastSensitivityMax = contrast_sensitivity(3.248f, 100.0f);
float pixelsPerDegree = width / (2.0f * tanf(fov * 0.5f) * 180.0f / SK_ScalarPI);
ImageL3D baselineL(width, height, maxLevels);
ImageL3D testL(width, height, maxLevels);
ImageL scratchImageL(width, height);
float* cyclesPerDegree = SkNEW_ARRAY(float, maxLevels);
float* thresholdFactorFrequency = SkNEW_ARRAY(float, maxLevels - 2);
float* contrast = SkNEW_ARRAY(float, maxLevels - 2);
lab_to_l(baselineLAB, baselineL.getLayer(0));
lab_to_l(testLAB, testL.getLayer(0));
// Compute cpd - Cycles per degree on the pyramid
cyclesPerDegree[0] = 0.5f * pixelsPerDegree;
for (int levelIndex = 1; levelIndex < maxLevels; levelIndex++) {
cyclesPerDegree[levelIndex] = cyclesPerDegree[levelIndex - 1] * 0.5f;
}
// Contrast sensitivity is based on image dimensions. Therefore it cannot be statically
// generated.
float* contrastSensitivityTable = SkNEW_ARRAY(float, maxLevels * 1000);
for (int levelIndex = 0; levelIndex < maxLevels; levelIndex++) {
for (int csLum = 0; csLum < 1000; csLum++) {
contrastSensitivityTable[levelIndex * 1000 + csLum] =
contrast_sensitivity(cyclesPerDegree[levelIndex], (float)csLum / 10.0f + 1e-5f);
}
}
// Compute G - The convolved lum for the baseline
for (int levelIndex = 1; levelIndex < maxLevels; levelIndex++) {
convolve(baselineL.getLayer(levelIndex - 1), false, &scratchImageL);
convolve(&scratchImageL, true, baselineL.getLayer(levelIndex));
}
for (int levelIndex = 1; levelIndex < maxLevels; levelIndex++) {
convolve(testL.getLayer(levelIndex - 1), false, &scratchImageL);
convolve(&scratchImageL, true, testL.getLayer(levelIndex));
}
// Compute F_freq - The elevation f
for (int levelIndex = 0; levelIndex < maxLevels - 2; levelIndex++) {
float cpd = cyclesPerDegree[levelIndex];
thresholdFactorFrequency[levelIndex] = contrastSensitivityMax /
contrast_sensitivity(cpd, 100.0f);
}
// Calculate F
for (int y = 0; y < height; y++) {
for (int x = 0; x < width; x++) {
float lBaseline;
float lTest;
baselineL.getLayer(0)->readPixel(x, y, &lBaseline);
testL.getLayer(0)->readPixel(x, y, &lTest);
float avgLBaseline;
float avgLTest;
baselineL.getLayer(maxLevels - 1)->readPixel(x, y, &avgLBaseline);
testL.getLayer(maxLevels - 1)->readPixel(x, y, &avgLTest);
float lAdapt = 0.5f * (avgLBaseline + avgLTest);
if (lAdapt < 1e-5f) {
lAdapt = 1e-5f;
}
float contrastSum = 0.0f;
for (int levelIndex = 0; levelIndex < maxLevels - 2; levelIndex++) {
float baselineL0, baselineL1, baselineL2;
float testL0, testL1, testL2;
baselineL.getLayer(levelIndex + 0)->readPixel(x, y, &baselineL0);
testL. getLayer(levelIndex + 0)->readPixel(x, y, &testL0);
baselineL.getLayer(levelIndex + 1)->readPixel(x, y, &baselineL1);
testL. getLayer(levelIndex + 1)->readPixel(x, y, &testL1);
baselineL.getLayer(levelIndex + 2)->readPixel(x, y, &baselineL2);
testL. getLayer(levelIndex + 2)->readPixel(x, y, &testL2);
float baselineContrast1 = fabsf(baselineL0 - baselineL1);
float testContrast1 = fabsf(testL0 - testL1);
float numerator = (baselineContrast1 > testContrast1) ?
baselineContrast1 : testContrast1;
float baselineContrast2 = fabsf(baselineL2);
float testContrast2 = fabsf(testL2);
float denominator = (baselineContrast2 > testContrast2) ?
baselineContrast2 : testContrast2;
// Avoid divides by close to zero
if (denominator < 1e-5f) {
denominator = 1e-5f;
}
contrast[levelIndex] = numerator / denominator;
contrastSum += contrast[levelIndex];
}
if (contrastSum < 1e-5f) {
contrastSum = 1e-5f;
}
float F = 0.0f;
for (int levelIndex = 0; levelIndex < maxLevels - 2; levelIndex++) {
float contrastSensitivity = contrastSensitivityTable[levelIndex * 1000 +
(int)(lAdapt * 10.0)];
float mask = SkPMetricUtil::get_visual_mask(contrast[levelIndex] *
contrastSensitivity);
F += contrast[levelIndex] +
thresholdFactorFrequency[levelIndex] * mask / contrastSum;
}
if (F < 1.0f) {
F = 1.0f;
}
if (F > 10.0f) {
F = 10.0f;
}
bool isFailure = false;
if (fabsf(lBaseline - lTest) > F * SkPMetricUtil::get_threshold_vs_intensity(lAdapt)) {
isFailure = true;
} else {
LAB baselineColor;
LAB testColor;
baselineLAB->readPixel(x, y, &baselineColor);
testLAB->readPixel(x, y, &testColor);
float contrastA = baselineColor.a - testColor.a;
float contrastB = baselineColor.b - testColor.b;
float colorScale = 1.0f;
if (lAdapt < 10.0f) {
colorScale = lAdapt / 10.0f;
}
colorScale *= colorScale;
if ((contrastA * contrastA + contrastB * contrastB) * colorScale > F)
{
isFailure = true;
}
}
if (isFailure) {
(*poiCount)++;
}
}
}
SkDELETE_ARRAY(cyclesPerDegree);
SkDELETE_ARRAY(contrast);
SkDELETE_ARRAY(thresholdFactorFrequency);
SkDELETE_ARRAY(contrastSensitivityTable);
return 1.0 - (double)(*poiCount) / (width * height);
}
bool SkPMetric::diff(SkBitmap* baseline, SkBitmap* test, bool computeMask, Result* result) const {
double startTime = get_seconds();
// Ensure the images are comparable
if (baseline->width() != test->width() || baseline->height() != test->height() ||
baseline->width() <= 0 || baseline->height() <= 0) {
return false;
}
ImageLAB baselineLAB(baseline->width(), baseline->height());
ImageLAB testLAB(baseline->width(), baseline->height());
if (!bitmap_to_cielab(baseline, &baselineLAB) || !bitmap_to_cielab(test, &testLAB)) {
return true;
}
result->poiCount = 0;
result->result = pmetric(&baselineLAB, &testLAB, &result->poiCount);
result->timeElapsed = get_seconds() - startTime;
return true;
}