ahd demosaic, reduced processing time and memory usage, #4698
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heckflosse
parent
6c8a47ebdf
commit
f3ecd14481
@ -2332,209 +2332,201 @@ void RawImageSource::igv_interpolate(int winw, int winh)
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/*
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Adaptive Homogeneity-Directed interpolation is based on
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the work of Keigo Hirakawa, Thomas Parks, and Paul Lee.
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Optimized for speed and reduced memory usage 2018 Ingo Weyrich
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*/
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#define TS 256 /* Tile Size */
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#define FORC(cnt) for (c=0; c < cnt; c++)
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#define FORC3 FORC(3)
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#define TS 144
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void RawImageSource::ahd_demosaic()
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{
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BENCHFUN
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int i, j, k, tr, tc, c, d, hm[2];
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float val;
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float (*pix)[3], (*rix)[3];
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static const int dir[4] = { -1, 1, -TS, TS };
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float ldiff[2][4], abdiff[2][4], leps, abeps;
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float xyz[3], xyz_cam[3][3];
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constexpr int dir[4] = { -1, 1, -TS, TS };
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float xyz_cam[3][3];
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LUTf cbrt(65536);
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float (*rgb)[TS][TS][3];
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float (*lab)[TS][TS][3];
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float (*lix)[3];
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char (*homo)[TS][TS], *buffer;
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double r;
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int width = W, height = H;
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unsigned int colors = 3;
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const double xyz_rgb[3][3] = { /* XYZ from RGB */
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constexpr double xyz_rgb[3][3] = { /* XYZ from RGB */
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{ 0.412453, 0.357580, 0.180423 },
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{ 0.212671, 0.715160, 0.072169 },
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{ 0.019334, 0.119193, 0.950227 }
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};
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const float d65_white[3] = { 0.950456, 1, 1.088754 };
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constexpr float d65_white[3] = { 0.950456, 1, 1.088754 };
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volatile double progress = 0.0;
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if (plistener) {
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plistener->setProgressStr (Glib::ustring::compose(M("TP_RAW_DMETHOD_PROGRESSBAR"), RAWParams::BayerSensor::getMethodString(RAWParams::BayerSensor::Method::AHD)));
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plistener->setProgress (0.0);
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}
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float (*image)[3] = (float (*)[3]) calloc (H * W, sizeof * image);
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for (int ii = 0; ii < H; ii++)
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for (int jj = 0; jj < W; jj++) {
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image[ii * W + jj][fc(ii, jj)] = rawData[ii][jj];
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}
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for (i = 0; i < 0x10000; i++) {
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r = (double)i / 65535.0;
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for (int i = 0; i < 0x10000; i++) {
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double r = (double)i / 65535.0;
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cbrt[i] = r > 0.008856 ? std::cbrt(r) : 7.787 * r + 16 / 116.0;
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}
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for (i = 0; i < 3; i++)
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for (unsigned int j = 0; j < colors; j++)
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for (xyz_cam[i][j] = k = 0; k < 3; k++) {
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for (int i = 0; i < 3; i++)
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for (unsigned int j = 0; j < 3; j++) {
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xyz_cam[i][j] = 0;
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for (int k = 0; k < 3; k++) {
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xyz_cam[i][j] += xyz_rgb[i][k] * imatrices.rgb_cam[k][j] / d65_white[i];
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}
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}
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border_interpolate(5, image);
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buffer = (char *) malloc (13 * TS * TS * sizeof(float)); /* 1664 kB */
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//merror (buffer, "ahd_interpolate()");
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rgb = (float(*)[TS][TS][3]) buffer;
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lab = (float(*)[TS][TS][3])(buffer + 6 * TS * TS * sizeof(float));
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homo = (char (*)[TS][TS]) (buffer + 12 * TS * TS * sizeof(float));
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border_interpolate2(W, H, 5, rawData, red, green, blue);
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// helper variables for progress indication
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int n_tiles = ((height - 7 + (TS - 7)) / (TS - 6)) * ((width - 7 + (TS - 7)) / (TS - 6));
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int tile = 0;
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#ifdef _OPENMP
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#pragma omp parallel
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#endif
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{
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int progresscounter = 0;
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float (*pix), (*rix)[3];
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float ldiff[2][4], abdiff[2][4];
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float (*lix)[3];
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char *buffer = (char *) malloc (12 * TS * TS * sizeof(float) + 2 * TS * TS * sizeof(uint16_t)); /* 1053 kB per core */
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float (*rgb)[TS][TS][3] = (float(*)[TS][TS][3]) buffer;
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float (*lab)[TS][TS][3] = (float(*)[TS][TS][3])(buffer + 6 * TS * TS * sizeof(float));
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uint16_t (*homo)[TS][TS] = (uint16_t(*)[TS][TS])(buffer + 12 * TS * TS * sizeof(float));
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for (int top = 2; top < height - 5; top += TS - 6)
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#ifdef _OPENMP
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#pragma omp for collapse(2) schedule(dynamic) nowait
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#endif
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for (int top = 2; top < height - 5; top += TS - 6) {
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for (int left = 2; left < width - 5; left += TS - 6) {
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/* Interpolate green horizontally and vertically: */
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// Interpolate green horizontally and vertically:
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for (int row = top; row < top + TS && row < height - 2; row++) {
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int col = left + (FC(row, left) & 1);
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for (c = FC(row, col); col < left + TS && col < width - 2; col += 2) {
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pix = image + (row * width + col);
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val = 0.25f * ((pix[-1][1] + pix[0][c] + pix[1][1]) * 2
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- pix[-2][c] - pix[2][c]) ;
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rgb[0][row - top][col - left][1] = median(val, pix[-1][1], pix[1][1]);
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val = 0.25f * ((pix[-width][1] + pix[0][c] + pix[width][1]) * 2
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- pix[-2 * width][c] - pix[2 * width][c]) ;
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rgb[1][row - top][col - left][1] = median(val, pix[-width][1], pix[width][1]);
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for (int col = left + (FC(row, left) & 1); col < std::min(left + TS, width - 2); col += 2) {
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pix = &(rawData[row][col]);
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float val0 = 0.25f * ((pix[-1] + pix[0] + pix[1]) * 2
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- pix[-2] - pix[2]) ;
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rgb[0][row - top][col - left][1] = median(val0, pix[-1], pix[1]);
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float val1 = 0.25f * ((pix[-width] + pix[0] + pix[width]) * 2
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- pix[-2 * width] - pix[2 * width]) ;
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rgb[1][row - top][col - left][1] = median(val1, pix[-width], pix[width]);
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}
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}
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/* Interpolate red and blue, and convert to CIELab: */
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for (d = 0; d < 2; d++)
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for (int row = top + 1; row < top + TS - 1 && row < height - 3; row++)
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for (int col = left + 1; col < left + TS - 1 && col < width - 3; col++) {
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pix = image + (row * width + col);
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// Interpolate red and blue, and convert to CIELab:
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for (int d = 0; d < 2; d++)
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for (int row = top + 1; row < top + TS - 1 && row < height - 3; row++) {
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int cng = FC(row + 1, FC(row + 1, 0) & 1);
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for (int col = left + 1; col < std::min(left + TS - 1, width - 3); col++) {
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pix = &(rawData[row][col]);
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rix = &rgb[d][row - top][col - left];
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lix = &lab[d][row - top][col - left];
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if ((c = 2 - FC(row, col)) == 1) {
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c = FC(row + 1, col);
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val = pix[0][1] + (0.5f * ( pix[-1][2 - c] + pix[1][2 - c]
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- rix[-1][1] - rix[1][1] ) );
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rix[0][2 - c] = CLIP(val);
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val = pix[0][1] + (0.5f * ( pix[-width][c] + pix[width][c]
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- rix[-TS][1] - rix[TS][1] ) );
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} else
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val = rix[0][1] + (0.25f * ( pix[-width - 1][c] + pix[-width + 1][c]
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+ pix[+width - 1][c] + pix[+width + 1][c]
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if (FC(row, col) == 1) {
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rix[0][2 - cng] = CLIP(pix[0] + (0.5f * (pix[-1] + pix[1]
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- rix[-1][1] - rix[1][1] ) ));
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rix[0][cng] = CLIP(pix[0] + (0.5f * (pix[-width] + pix[width]
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- rix[-TS][1] - rix[TS][1])));
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rix[0][1] = pix[0];
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} else {
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rix[0][cng] = CLIP(rix[0][1] + (0.25f * (pix[-width - 1] + pix[-width + 1]
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+ pix[+width - 1] + pix[+width + 1]
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- rix[-TS - 1][1] - rix[-TS + 1][1]
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- rix[+TS - 1][1] - rix[+TS + 1][1]) );
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rix[0][c] = CLIP(val);
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c = FC(row, col);
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rix[0][c] = pix[0][c];
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xyz[0] = xyz[1] = xyz[2] = 0.f;
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FORCC {
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xyz[0] += xyz_cam[0][c] * rix[0][c];
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xyz[1] += xyz_cam[1][c] * rix[0][c];
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xyz[2] += xyz_cam[2][c] * rix[0][c];
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- rix[+TS - 1][1] - rix[+TS + 1][1])));
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rix[0][2 - cng] = pix[0];
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}
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float xyz0 = 0.f;
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float xyz1 = 0.f;
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float xyz2 = 0.f;
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for(unsigned int c = 0; c < 3; ++c) {
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xyz0 += xyz_cam[0][c] * rix[0][c];
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xyz1 += xyz_cam[1][c] * rix[0][c];
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xyz2 += xyz_cam[2][c] * rix[0][c];
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}
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xyz[0] = cbrt[xyz[0]];
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xyz[1] = cbrt[xyz[1]];
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xyz[2] = cbrt[xyz[2]];
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xyz0 = cbrt[xyz0];
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xyz1 = cbrt[xyz1];
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xyz2 = cbrt[xyz2];
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//xyz[0] = xyz[0] > 0.008856 ? pow(xyz[0]/65535,1/3.0) : 7.787*xyz[0] + 16/116.0;
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//xyz[1] = xyz[1] > 0.008856 ? pow(xyz[1]/65535,1/3.0) : 7.787*xyz[1] + 16/116.0;
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//xyz[2] = xyz[2] > 0.008856 ? pow(xyz[2]/65535,1/3.0) : 7.787*xyz[2] + 16/116.0;
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lix[0][0] = (116 * xyz[1] - 16);
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lix[0][1] = 500 * (xyz[0] - xyz[1]);
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lix[0][2] = 200 * (xyz[1] - xyz[2]);
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lix[0][0] = 116.f * xyz1 - 16.f;
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lix[0][1] = 500.f * (xyz0 - xyz1);
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lix[0][2] = 200.f * (xyz1 - xyz2);
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}
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}
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/* Build homogeneity maps from the CIELab images: */
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memset (homo, 0, 2 * TS * TS);
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// Build homogeneity maps from the CIELab images:
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for (int row = top + 2; row < top + TS - 2 && row < height - 4; row++) {
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tr = row - top;
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int tr = row - top;
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for (int col = left + 2; col < left + TS - 2 && col < width - 4; col++) {
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tc = col - left;
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for (d = 0; d < 2; d++) {
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for (int col = left + 2, tc = 2; col < left + TS - 2 && col < width - 4; col++, tc++) {
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for (int d = 0; d < 2; d++) {
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lix = &lab[d][tr][tc];
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for (i = 0; i < 4; i++) {
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for (int i = 0; i < 4; i++) {
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ldiff[d][i] = std::fabs(lix[0][0] - lix[dir[i]][0]);
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abdiff[d][i] = SQR(lix[0][1] - lix[dir[i]][1])
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+ SQR(lix[0][2] - lix[dir[i]][2]);
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}
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}
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leps = min(max(ldiff[0][0], ldiff[0][1]),
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max(ldiff[1][2], ldiff[1][3]));
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abeps = min(max(abdiff[0][0], abdiff[0][1]),
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max(abdiff[1][2], abdiff[1][3]));
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float leps = min(max(ldiff[0][0], ldiff[0][1]),
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max(ldiff[1][2], ldiff[1][3]));
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float abeps = min(max(abdiff[0][0], abdiff[0][1]),
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max(abdiff[1][2], abdiff[1][3]));
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for (d = 0; d < 2; d++)
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for (i = 0; i < 4; i++)
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for (int d = 0; d < 2; d++) {
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homo[d][tr][tc] = 0;
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for (int i = 0; i < 4; i++) {
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if (ldiff[d][i] <= leps && abdiff[d][i] <= abeps) {
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homo[d][tr][tc]++;
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}
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}
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}
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}
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}
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/* Combine the most homogenous pixels for the final result: */
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// Combine the most homogenous pixels for the final result:
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for (int row = top + 3; row < top + TS - 3 && row < height - 5; row++) {
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tr = row - top;
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int tr = row - top;
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for (int col = left + 3; col < left + TS - 3 && col < width - 5; col++) {
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tc = col - left;
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for (int col = left + 3, tc = 3; col < std::min(left + TS - 3, width - 5); col++, tc++) {
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uint16_t hm0 = 0, hm1 = 0;
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for (int i = tr - 1; i <= tr + 1; i++)
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for (int j = tc - 1; j <= tc + 1; j++) {
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hm0 += homo[0][i][j];
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hm1 += homo[1][i][j];
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}
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for (d = 0; d < 2; d++)
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for (hm[d] = 0, i = tr - 1; i <= tr + 1; i++)
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for (j = tc - 1; j <= tc + 1; j++) {
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hm[d] += homo[d][i][j];
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}
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if (hm[0] != hm[1]) {
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FORC3 image[row * width + col][c] = rgb[hm[1] > hm[0]][tr][tc][c];
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} else
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FORC3 image[row * width + col][c] =
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0.5f * (rgb[0][tr][tc][c] + rgb[1][tr][tc][c]) ;
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if (hm0 != hm1) {
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int dir = hm1 > hm0;
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red[row][col] = rgb[dir][tr][tc][0];
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green[row][col] = rgb[dir][tr][tc][1];
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blue[row][col] = rgb[dir][tr][tc][2];
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} else {
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red[row][col] = 0.5f * (rgb[0][tr][tc][0] + rgb[1][tr][tc][0]);
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green[row][col] = 0.5f * (rgb[0][tr][tc][1] + rgb[1][tr][tc][1]);
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blue[row][col] = 0.5f * (rgb[0][tr][tc][2] + rgb[1][tr][tc][2]);
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}
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}
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}
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tile++;
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if(plistener) {
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plistener->setProgress((double)tile / n_tiles);
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}
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}
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progresscounter++;
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if(progresscounter % 32 == 0) {
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#ifdef _OPENMP
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#pragma omp critical (ahdprogress)
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#endif
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{
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progress += (double)32 * ((TS - 32) * (TS - 32)) / (height * width);
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progress = progress > 1.0 ? 1.0 : progress;
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plistener->setProgress(progress);
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}
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}
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}
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}
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}
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free (buffer);
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}
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if(plistener) {
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plistener->setProgress (1.0);
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}
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free (buffer);
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for (int i = 0; i < H; i++) {
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for (int j = 0; j < W; j++) {
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red[i][j] = image[i * W + j][0];
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green[i][j] = image[i * W + j][1];
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blue[i][j] = image[i * W + j][2];
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}
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}
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free (image);
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}
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#undef TS
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