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Capture sharpening: improve auto radius calculation for xtrans

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This commit is contained in:
Ingo Weyrich 2019-11-16 16:06:31 +01:00
parent c2ed31991b
commit f041573d4d
1 changed files with 101 additions and 11 deletions
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96
rtengine/capturesharpening.cc
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@ -409,8 +409,85 @@ float calcRadiusXtrans(const float * const *rawData, int W, int H, float lowerLi
#ifdef _OPENMP #ifdef _OPENMP
#pragma omp parallel for reduction(max:maxRatio) schedule(dynamic, 16) #pragma omp parallel for reduction(max:maxRatio) schedule(dynamic, 16)
#endif #endif
for (int row = starty + 3; row < H - 4; row += 3) { for (int row = starty + 2; row < H - 4; row += 3) {
for (int col = startx + 3; col < W - 4; col += 3) { for (int col = startx + 2; col < W - 4; col += 3) {
const float valp1p1 = rawData[row + 1][col + 1];
const bool squareClipped = rtengine::max(valp1p1, rawData[row + 1][col + 2], rawData[row + 2][col + 1], rawData[row + 2][col + 2]) >= upperLimit;
const float greenSolitary = rawData[row][col];
if (greenSolitary > 1.f && std::max(rawData[row - 1][col - 1], rawData[row - 1][col + 1]) < upperLimit) {
if (greenSolitary < upperLimit) {
const float valp1m1 = rawData[row + 1][col - 1];
if (valp1m1 > 1.f && rtengine::max(rawData[row + 1][col - 2], valp1m1, rawData[row + 2][col - 2], rawData[row + 1][col - 1]) < upperLimit) {
const float maxVal = std::max(greenSolitary, valp1m1);
if (maxVal > lowerLimit) {
const float minVal = std::min(greenSolitary, valp1m1);
if (UNLIKELY(maxVal > maxRatio * minVal)) {
maxRatio = maxVal / minVal;
}
}
}
if (valp1p1 > 1.f && !squareClipped) {
const float maxVal = std::max(greenSolitary, valp1p1);
if (maxVal > lowerLimit) {
const float minVal = std::min(greenSolitary, valp1p1);
if (UNLIKELY(maxVal > maxRatio * minVal)) {
maxRatio = maxVal / minVal;
}
}
}
}
}
if (!squareClipped) {
const float valp2p2 = rawData[row + 2][col + 2];
if (valp2p2 > 1.f) {
if (valp1p1 > 1.f) {
const float maxVal = std::max(valp1p1, valp2p2);
if (maxVal > lowerLimit) {
const float minVal = std::min(valp1p1, valp2p2);
if (UNLIKELY(maxVal > maxRatio * minVal)) {
maxRatio = maxVal / minVal;
}
}
}
const float greenSolitaryRight = rawData[row + 3][col + 3];
if (rtengine::max(greenSolitaryRight, rawData[row + 4][col + 2], rawData[row + 4][col + 4]) < upperLimit) {
if (greenSolitaryRight > 1.f) {
const float maxVal = std::max(greenSolitaryRight, valp2p2);
if (maxVal > lowerLimit) {
const float minVal = std::min(greenSolitaryRight, valp2p2);
if (UNLIKELY(maxVal > maxRatio * minVal)) {
maxRatio = maxVal / minVal;
}
}
}
}
}
const float valp1p2 = rawData[row + 1][col + 2];
const float valp2p1 = rawData[row + 2][col + 1];
if (valp2p1 > 1.f) {
if (valp1p2 > 1.f) {
const float maxVal = std::max(valp1p2, valp2p1);
if (maxVal > lowerLimit) {
const float minVal = std::min(valp1p2, valp2p1);
if (UNLIKELY(maxVal > maxRatio * minVal)) {
maxRatio = maxVal / minVal;
}
}
}
const float greenSolitaryLeft = rawData[row + 3][col];
if (rtengine::max(greenSolitaryLeft, rawData[row + 4][col - 1], rawData[row + 4][col + 1]) < upperLimit) {
if (greenSolitaryLeft > 1.f) {
const float maxVal = std::max(greenSolitaryLeft, valp2p1);
if (maxVal > lowerLimit) {
const float minVal = std::min(greenSolitaryLeft, valp2p1);
if (UNLIKELY(maxVal > maxRatio * minVal)) {
maxRatio = maxVal / minVal;
}
}
}
}
}
}
const float valtl = rawData[row][col]; const float valtl = rawData[row][col];
const float valtr = rawData[row][col + 1]; const float valtr = rawData[row][col + 1];
const float valbl = rawData[row + 1][col]; const float valbl = rawData[row + 1][col];
@ -494,7 +571,7 @@ float calcRadiusXtrans(const float * const *rawData, int W, int H, float lowerLi
} }
} }
} }
return std::sqrt((1.f / (std::log(1.f / maxRatio))) / -2.f); return std::sqrt((1.f / (std::log(1.f / maxRatio) / 2.f)) / -2.f);
} }
bool checkForStop(float** tmpIThr, float** iterCheck, int fullTileSize, int border) bool checkForStop(float** tmpIThr, float** iterCheck, int fullTileSize, int border)
@ -618,6 +695,7 @@ BENCHFUN
const float distance = sqrt(rtengine::SQR(i + tileSize / 2 - H / 2) + rtengine::SQR(j + tileSize / 2 - W / 2)); const float distance = sqrt(rtengine::SQR(i + tileSize / 2 - H / 2) + rtengine::SQR(j + tileSize / 2 - W / 2));
const float sigmaTile = static_cast<float>(sigma) + distanceFactor * distance; const float sigmaTile = static_cast<float>(sigma) + distanceFactor * distance;
if (sigmaTile >= 0.4f) { if (sigmaTile >= 0.4f) {
if (sigmaTile > 0.84) { // have to use 7x7 kernel
float lkernel7[7][7]; float lkernel7[7][7];
compute7x7kernel(static_cast<float>(sigma) + distanceFactor * distance, lkernel7); compute7x7kernel(static_cast<float>(sigma) + distanceFactor * distance, lkernel7);
for (int k = 0; k < iterations && !stopped; ++k) { for (int k = 0; k < iterations && !stopped; ++k) {
@ -628,6 +706,18 @@ BENCHFUN
stopped = checkForStop(tmpIThr, iterCheck, fullTileSize, border); stopped = checkForStop(tmpIThr, iterCheck, fullTileSize, border);
} }
} }
} else { // can use 5x5 kernel
float lkernel7[5][5];
compute5x5kernel(static_cast<float>(sigma) + distanceFactor * distance, lkernel7);
for (int k = 0; k < iterations && !stopped; ++k) {
// apply 7x7 gaussian blur and divide luminance by result of gaussian blur
gauss5x5div(tmpIThr, tmpThr, lumThr, fullTileSize, lkernel7);
gauss5x5mult(tmpThr, tmpIThr, fullTileSize, lkernel7);
if (checkIterStop) {
stopped = checkForStop(tmpIThr, iterCheck, fullTileSize, border);
}
}
}
} }
} else { } else {
for (int k = 0; k < iterations && !stopped; ++k) { for (int k = 0; k < iterations && !stopped; ++k) {