diff --git a/rtengine/rcd_demosaic.cc b/rtengine/rcd_demosaic.cc index 6587d3930..624b309b1 100644 --- a/rtengine/rcd_demosaic.cc +++ b/rtengine/rcd_demosaic.cc @@ -1,7 +1,7 @@ /* * This file is part of RawTherapee. * - * Copyright (c) 2017-2018 Luis Sanz Rodriguez (luis.sanz.rodriguez(at)gmail(dot)com) and Ingo Weyrich (heckflosse67@gmx.de) + * Copyright (c) 2017-2020 Luis Sanz Rodriguez (luis.sanz.rodriguez(at)gmail(dot)com) and Ingo Weyrich (heckflosse67@gmx.de) * * RawTherapee is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by @@ -82,8 +82,8 @@ void RawImageSource::rcd_demosaic(size_t chunkSize, bool measure) const int numTw = W / (tileSizeN) + ((W % (tileSizeN)) ? 1 : 0); constexpr int w1 = tileSize, w2 = 2 * tileSize, w3 = 3 * tileSize, w4 = 4 * tileSize; //Tolerance to avoid dividing by zero - static constexpr float eps = 1e-5f; - static constexpr float epssq = 1e-10f; + constexpr float eps = 1e-5f; + constexpr float epssq = 1e-10f; #ifdef _OPENMP #pragma omp parallel @@ -99,16 +99,16 @@ void RawImageSource::rcd_demosaic(size_t chunkSize, bool measure) #ifdef _OPENMP #pragma omp for schedule(dynamic, chunkSize) collapse(2) nowait #endif - for(int tr = 0; tr < numTh; ++tr) { - for(int tc = 0; tc < numTw; ++tc) { + for (int tr = 0; tr < numTh; ++tr) { + for (int tc = 0; tc < numTw; ++tc) { const int rowStart = tr * tileSizeN; const int rowEnd = std::min(rowStart + tileSize, H); - if(rowStart + rcdBorder == rowEnd - rcdBorder) { + if (rowStart + rcdBorder == rowEnd - rcdBorder) { continue; } const int colStart = tc * tileSizeN; const int colEnd = std::min(colStart + tileSize, W); - if(colStart + rcdBorder == colEnd - rcdBorder) { + if (colStart + rcdBorder == colEnd - rcdBorder) { continue; } @@ -125,7 +125,7 @@ void RawImageSource::rcd_demosaic(size_t chunkSize, bool measure) cfa[indx] = rgb[c0][indx] = LIM01(rawData[row][col] / 65535.f); cfa[indx + 1] = rgb[c1][indx + 1] = LIM01(rawData[row][col + 1] / 65535.f); } - if(col < colEnd) { + if (col < colEnd) { cfa[indx] = rgb[c0][indx] = LIM01(rawData[row][col] / 65535.f); } } @@ -160,36 +160,68 @@ void RawImageSource::rcd_demosaic(size_t chunkSize, bool measure) * STEP 3: Populate the green channel */ // Step 3.1: Populate the green channel at blue and red CFA positions - for (int row = 4; row < tileRows - 4; row++) { - for (int col = 4 + (fc(cfarray, row, 0) & 1), indx = row * tileSize + col; col < tilecols - 4; col += 2, indx += 2) { + for (int row = 4; row < tileRows - 4; row++) { + int col = 4 + (fc(cfarray, row, 0) & 1); + int indx = row * tileSize + col; - // Refined vertical and horizontal local discrimination - float VH_Central_Value = VH_Dir[indx]; - float VH_Neighbourhood_Value = 0.25f * ((VH_Dir[indx - w1 - 1] + VH_Dir[indx - w1 + 1]) + (VH_Dir[indx + w1 - 1] + VH_Dir[indx + w1 + 1])); - - float VH_Disc = std::fabs(0.5f - VH_Central_Value) < std::fabs(0.5f - VH_Neighbourhood_Value) ? VH_Neighbourhood_Value : VH_Central_Value; - - // Cardinal gradients - float N_Grad = eps + std::fabs(cfa[indx - w1] - cfa[indx + w1]) + std::fabs(cfa[indx] - cfa[indx - w2]) + std::fabs(cfa[indx - w1] - cfa[indx - w3]) + std::fabs(cfa[indx - w2] - cfa[indx - w4]); - float S_Grad = eps + std::fabs(cfa[indx - w1] - cfa[indx + w1]) + std::fabs(cfa[indx] - cfa[indx + w2]) + std::fabs(cfa[indx + w1] - cfa[indx + w3]) + std::fabs(cfa[indx + w2] - cfa[indx + w4]); - float W_Grad = eps + std::fabs(cfa[indx - 1] - cfa[indx + 1]) + std::fabs(cfa[indx] - cfa[indx - 2]) + std::fabs(cfa[indx - 1] - cfa[indx - 3]) + std::fabs(cfa[indx - 2] - cfa[indx - 4]); - float E_Grad = eps + std::fabs(cfa[indx - 1] - cfa[indx + 1]) + std::fabs(cfa[indx] - cfa[indx + 2]) + std::fabs(cfa[indx + 1] - cfa[indx + 3]) + std::fabs(cfa[indx + 2] - cfa[indx + 4]); +#ifdef __SSE2__ + for (; col < tilecols - 7; col += 8, indx += 8) { + // Cardinal gradients + const vfloat cfai = LC2VFU(cfa[indx]); + const vfloat N_Grad = eps + (vabsf(LC2VFU(cfa[indx - w1]) - LC2VFU(cfa[indx + w1])) + vabsf(cfai - LC2VFU(cfa[indx - w2]))) + (vabsf(LC2VFU(cfa[indx - w1]) - LC2VFU(cfa[indx - w3])) + vabsf(LC2VFU(cfa[indx - w2]) - LC2VFU(cfa[indx - w4]))); + const vfloat S_Grad = eps + (vabsf(LC2VFU(cfa[indx - w1]) - LC2VFU(cfa[indx + w1])) + vabsf(cfai - LC2VFU(cfa[indx + w2]))) + (vabsf(LC2VFU(cfa[indx + w1]) - LC2VFU(cfa[indx + w3])) + vabsf(LC2VFU(cfa[indx + w2]) - LC2VFU(cfa[indx + w4]))); + const vfloat W_Grad = eps + (vabsf(LC2VFU(cfa[indx - 1]) - LC2VFU(cfa[indx + 1])) + vabsf(cfai - LC2VFU(cfa[indx - 2]))) + (vabsf(LC2VFU(cfa[indx - 1]) - LC2VFU(cfa[indx - 3])) + vabsf(LC2VFU(cfa[indx - 2]) - LC2VFU(cfa[indx - 4]))); + const vfloat E_Grad = eps + (vabsf(LC2VFU(cfa[indx - 1]) - LC2VFU(cfa[indx + 1])) + vabsf(cfai - LC2VFU(cfa[indx + 2]))) + (vabsf(LC2VFU(cfa[indx + 1]) - LC2VFU(cfa[indx + 3])) + vabsf(LC2VFU(cfa[indx + 2]) - LC2VFU(cfa[indx + 4]))); // Cardinal pixel estimations - float N_Est = cfa[indx - w1] * (1.f + (lpf[indx>>1] - lpf[(indx - w2)>>1]) / (eps + lpf[indx>>1] + lpf[(indx - w2)>>1])); - float S_Est = cfa[indx + w1] * (1.f + (lpf[indx>>1] - lpf[(indx + w2)>>1]) / (eps + lpf[indx>>1] + lpf[(indx + w2)>>1])); - float W_Est = cfa[indx - 1] * (1.f + (lpf[indx>>1] - lpf[(indx - 2)>>1]) / (eps + lpf[indx>>1] + lpf[(indx - 2)>>1])); - float E_Est = cfa[indx + 1] * (1.f + (lpf[indx>>1] - lpf[(indx + 2)>>1]) / (eps + lpf[indx>>1] + lpf[(indx + 2)>>1])); + const vfloat lpfi = LVFU(lpf[indx>>1]); + const vfloat N_Est = LC2VFU(cfa[indx - w1]) + (LC2VFU(cfa[indx - w1]) * (lpfi - LVFU(lpf[(indx - w2)>>1])) / (eps + lpfi + LVFU(lpf[(indx - w2)>>1]))); + const vfloat S_Est = LC2VFU(cfa[indx + w1]) + (LC2VFU(cfa[indx + w1]) * (lpfi - LVFU(lpf[(indx + w2)>>1])) / (eps + lpfi + LVFU(lpf[(indx + w2)>>1]))); + const vfloat W_Est = LC2VFU(cfa[indx - 1]) + (LC2VFU(cfa[indx - 1]) * (lpfi - LVFU(lpf[(indx - 2)>>1])) / (eps + lpfi + LVFU(lpf[(indx - 2)>>1]))); + const vfloat E_Est = LC2VFU(cfa[indx + 1]) + (LC2VFU(cfa[indx + 1]) * (lpfi - LVFU(lpf[(indx + 2)>>1])) / (eps + lpfi + LVFU(lpf[(indx + 2)>>1]))); // Vertical and horizontal estimations - float V_Est = (S_Grad * N_Est + N_Grad * S_Est) / (N_Grad + S_Grad); - float H_Est = (W_Grad * E_Est + E_Grad * W_Est) / (E_Grad + W_Grad); + const vfloat V_Est = (S_Grad * N_Est + N_Grad * S_Est) / (N_Grad + S_Grad); + const vfloat H_Est = (W_Grad * E_Est + E_Grad * W_Est) / (E_Grad + W_Grad); // G@B and G@R interpolation - rgb[1][indx] = VH_Disc * H_Est + (1.f - VH_Disc) * V_Est; + // Refined vertical and horizontal local discrimination + const vfloat VH_Central_Value = LC2VFU(VH_Dir[indx]); + const vfloat VH_Neighbourhood_Value = 0.25f * ((LC2VFU(VH_Dir[indx - w1 - 1]) + LC2VFU(VH_Dir[indx - w1 + 1])) + (LC2VFU(VH_Dir[indx + w1 - 1]) + LC2VFU(VH_Dir[indx + w1 + 1]))); + const vfloat VH_Disc = vabsf(0.5f - VH_Central_Value) < vabsf(0.5f - VH_Neighbourhood_Value) ? VH_Neighbourhood_Value : VH_Central_Value; + STC2VFU(rgb[1][indx], vintpf(VH_Disc, H_Est, V_Est)); + } +#endif + for (; col < tilecols - 4; col += 2, indx += 2) { + // Cardinal gradients + const float cfai = cfa[indx]; + const float N_Grad = eps + (std::fabs(cfa[indx - w1] - cfa[indx + w1]) + std::fabs(cfai - cfa[indx - w2])) + (std::fabs(cfa[indx - w1] - cfa[indx - w3]) + std::fabs(cfa[indx - w2] - cfa[indx - w4])); + const float S_Grad = eps + (std::fabs(cfa[indx - w1] - cfa[indx + w1]) + std::fabs(cfai - cfa[indx + w2])) + (std::fabs(cfa[indx + w1] - cfa[indx + w3]) + std::fabs(cfa[indx + w2] - cfa[indx + w4])); + const float W_Grad = eps + (std::fabs(cfa[indx - 1] - cfa[indx + 1]) + std::fabs(cfai - cfa[indx - 2])) + (std::fabs(cfa[indx - 1] - cfa[indx - 3]) + std::fabs(cfa[indx - 2] - cfa[indx - 4])); + const float E_Grad = eps + (std::fabs(cfa[indx - 1] - cfa[indx + 1]) + std::fabs(cfai - cfa[indx + 2])) + (std::fabs(cfa[indx + 1] - cfa[indx + 3]) + std::fabs(cfa[indx + 2] - cfa[indx + 4])); + + // Cardinal pixel estimations + const float lpfi = lpf[indx>>1]; + const float N_Est = cfa[indx - w1] * (1.f + (lpfi - lpf[(indx - w2)>>1]) / (eps + lpfi + lpf[(indx - w2)>>1])); + const float S_Est = cfa[indx + w1] * (1.f + (lpfi - lpf[(indx + w2)>>1]) / (eps + lpfi + lpf[(indx + w2)>>1])); + const float W_Est = cfa[indx - 1] * (1.f + (lpfi - lpf[(indx - 2)>>1]) / (eps + lpfi + lpf[(indx - 2)>>1])); + const float E_Est = cfa[indx + 1] * (1.f + (lpfi - lpf[(indx + 2)>>1]) / (eps + lpfi + lpf[(indx + 2)>>1])); + + // Vertical and horizontal estimations + const float V_Est = (S_Grad * N_Est + N_Grad * S_Est) / (N_Grad + S_Grad); + const float H_Est = (W_Grad * E_Est + E_Grad * W_Est) / (E_Grad + W_Grad); + + // G@B and G@R interpolation + // Refined vertical and horizontal local discrimination + const float VH_Central_Value = VH_Dir[indx]; + const float VH_Neighbourhood_Value = 0.25f * ((VH_Dir[indx - w1 - 1] + VH_Dir[indx - w1 + 1]) + (VH_Dir[indx + w1 - 1] + VH_Dir[indx + w1 + 1])); + + const float VH_Disc = std::fabs(0.5f - VH_Central_Value) < std::fabs(0.5f - VH_Neighbourhood_Value) ? VH_Neighbourhood_Value : VH_Central_Value; + rgb[1][indx] = VH_Disc * H_Est + (1.f - VH_Disc) * V_Est; } } + /** * STEP 4: Populate the red and blue channels */ @@ -203,7 +235,6 @@ void RawImageSource::rcd_demosaic(size_t chunkSize, bool measure) float Q_Stat = max(epssq, - 18.f * cfai * (cfa[indx + w1 - 1] + cfa[indx - w1 + 1] + 2.f * (cfa[indx + w2 - 2] + cfa[indx - w2 + 2]) - cfa[indx + w3 - 3] - cfa[indx - w3 + 3]) - 2.f * cfai * (cfa[indx + w4 - 4] + cfa[indx - w4 + 4] - 19.f * cfai) - cfa[indx + w1 - 1] * (70.f * cfa[indx - w1 + 1] - 12.f * cfa[indx + w2 - 2] + 24.f * cfa[indx - w2 + 2] - 38.f * cfa[indx + w3 - 3] + 16.f * cfa[indx - w3 + 3] + 12.f * cfa[indx + w4 - 4] - 6.f * cfa[indx - w4 + 4] + 46.f * cfa[indx + w1 - 1]) + cfa[indx - w1 + 1] * (24.f * cfa[indx + w2 - 2] - 12.f * cfa[indx - w2 + 2] + 16.f * cfa[indx + w3 - 3] - 38.f * cfa[indx - w3 + 3] - 6.f * cfa[indx + w4 - 4] + 12.f * cfa[indx - w4 + 4] + 46.f * cfa[indx - w1 + 1]) + cfa[indx + w2 - 2] * (14.f * cfa[indx - w2 + 2] - 12.f * cfa[indx - w3 + 3] - 2.f * (cfa[indx + w4 - 4] - cfa[indx - w4 + 4]) + 11.f * cfa[indx + w2 - 2]) - cfa[indx - w2 + 2] * (12.f * cfa[indx + w3 - 3] + 2.f * (cfa[indx + w4 - 4] - cfa[indx - w4 + 4]) + 11.f * cfa[indx - w2 + 2]) + cfa[indx + w3 - 3] * (2.f * cfa[indx - w3 + 3] - 6.f * cfa[indx + w4 - 4] + 10.f * cfa[indx + w3 - 3]) - cfa[indx - w3 + 3] * (6.f * cfa[indx - w4 + 4] + 10.f * cfa[indx - w3 + 3]) + cfa[indx + w4 - 4] * cfa[indx + w4 - 4] + cfa[indx - w4 + 4] * cfa[indx - w4 + 4]); PQ_Dir[indx] = P_Stat / (P_Stat + Q_Stat); - } } @@ -235,7 +266,6 @@ void RawImageSource::rcd_demosaic(size_t chunkSize, bool measure) // R@B and B@R interpolation rgb[c][indx] = rgb[1][indx] + (1.f - PQ_Disc) * P_Est + PQ_Disc * Q_Est; - } } @@ -279,7 +309,6 @@ void RawImageSource::rcd_demosaic(size_t chunkSize, bool measure) // R@G and B@G interpolation rgb[c][indx] = rgb1 + (1.f - VH_Disc) * V_Est + VH_Disc * H_Est; - } } } @@ -293,9 +322,9 @@ void RawImageSource::rcd_demosaic(size_t chunkSize, bool measure) } } - if(plistener) { + if (plistener) { progresscounter++; - if(progresscounter % 32 == 0) { + if (progresscounter % 32 == 0) { #ifdef _OPENMP #pragma omp critical (rcdprogress) #endif @@ -306,7 +335,6 @@ void RawImageSource::rcd_demosaic(size_t chunkSize, bool measure) } } } - } } @@ -321,7 +349,6 @@ void RawImageSource::rcd_demosaic(size_t chunkSize, bool measure) if (plistener) { plistener->setProgress(1); } - // ------------------------------------------------------------------------- } } /* namespace */