/* * This file is part of RawTherapee. * * Copyright (c) 2004-2010 Gabor Horvath * * RawTherapee is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * RawTherapee is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with RawTherapee. If not, see . * adaptation to RawTherapee * 2015 Jacques Desmis * 2015 Ingo Weyrich * D. J. Jobson, Z. Rahman, and G. A. Woodell. A multi-scale * Retinex for bridging the gap between color images and the * human observation of scenes. IEEE Transactions on Image Processing, * 1997, 6(7): 965-976 * Fan Guo Zixing Cai Bin Xie Jin Tang * School of Information Science and Engineering, Central South University Changsha, China * Weixing Wang and Lian Xu * College of Physics and Information Engineering, Fuzhou University, Fuzhou, China * inspired from 2003 Fabien Pelisson * some ideas taken (use of mask) Russell Cottrell - The Retinex .8bf Plugin */ #include #include #include #include #include "gauss.h" #include "improcfun.h" #include "median.h" #include "opthelper.h" #include "procparams.h" #include "rawimagesource.h" #include "rtengine.h" #include "StopWatch.h" #define clipretinex( val, minv, maxv ) (( val = (val < minv ? minv : val ) ) > maxv ? maxv : val ) namespace { void retinex_scales( float* scales, int nscales, int mode, int s, float high) { if ( nscales == 1 ) { scales[0] = (float)s / 2.f; } else if (nscales == 2) { scales[1] = (float) s / 2.f; scales[0] = (float) s; } else { float size_step = (float) s / (float) nscales; if (mode == 0) { for (int i = 0; i < nscales; ++i ) { scales[nscales - i - 1] = 2.0f + (float)i * size_step; } } else if (mode == 1) { size_step = (float)log(s - 2.0f) / (float) nscales; for (int i = 0; i < nscales; ++i ) { scales[nscales - i - 1] = 2.0f + (float)pow (10.f, (i * size_step) / log (10.f)); } } else if (mode == 2) { size_step = (float) log(s - 2.0f) / (float) nscales; for ( int i = 0; i < nscales; ++i ) { scales[i] = s - (float)pow (10.f, (i * size_step) / log (10.f)); } } else if (mode == 3) { size_step = (float) log(s - 2.0f) / (float) nscales; for ( int i = 0; i < nscales; ++i ) { scales[i] = high * s - (float)pow (10.f, (i * size_step) / log (10.f)); } } } } void mean_stddv2( float **dst, float &mean, float &stddv, int W_L, int H_L, float &maxtr, float &mintr) { // summation using double precision to avoid too large summation error for large pictures double vsquared = 0.f; double sum = 0.f; maxtr = -999999.f; mintr = 999999.f; #ifdef _OPENMP #pragma omp parallel #endif { float lmax = -999999.f, lmin = 999999.f; #ifdef _OPENMP #pragma omp for reduction(+:sum,vsquared) nowait // this leads to differences, but parallel summation is more accurate #endif for (int i = 0; i < H_L; i++ ) for (int j = 0; j < W_L; j++) { sum += dst[i][j]; vsquared += (dst[i][j] * dst[i][j]); lmax = dst[i][j] > lmax ? dst[i][j] : lmax; lmin = dst[i][j] < lmin ? dst[i][j] : lmin; } #ifdef _OPENMP #pragma omp critical #endif { maxtr = maxtr > lmax ? maxtr : lmax; mintr = mintr < lmin ? mintr : lmin; } } mean = sum / (double) (W_L * H_L); vsquared /= (double) W_L * H_L; stddv = ( vsquared - (mean * mean) ); stddv = (float)sqrt(stddv); } } namespace rtengine { extern const Settings* settings; void RawImageSource::MSR(float** luminance, float** originalLuminance, float **exLuminance, LUTf & mapcurve, bool &mapcontlutili, int width, int height, const RetinexParams &deh, const RetinextransmissionCurve & dehatransmissionCurve, const RetinexgaintransmissionCurve & dehagaintransmissionCurve, float &minCD, float &maxCD, float &mini, float &maxi, float &Tmean, float &Tsigma, float &Tmin, float &Tmax) { if (deh.enabled) {//enabled float maxtr, mintr; constexpr float eps = 2.f; bool useHsl = deh.retinexcolorspace == "HSLLOG"; bool useHslLin = deh.retinexcolorspace == "HSLLIN"; float offse = (float) deh.offs; //def = 0 not use int iter = deh.iter; int gradient = deh.scal; int scal = 3;//disabled scal int nei = (int) (2.8f * deh.neigh); //def = 220 float vart = (float)deh.vart / 100.f;//variance float gradvart = (float)deh.grad; float gradstr = (float)deh.grads; float strength = (float) deh.str / 100.f; // Blend with original L channel data float limD = (float) deh.limd; limD = pow(limD, 1.7f);//about 2500 enough limD *= useHslLin ? 10.f : 1.f; float ilimD = 1.f / limD; float hig = ((float) deh.highl) / 100.f; scal = deh.skal; int H_L = height; int W_L = width; float *tran[H_L] ALIGNED16; float *tranBuffer = nullptr; constexpr float elogt = 2.71828f; bool lhutili = false; FlatCurve* shcurve = new FlatCurve(deh.lhcurve); //curve L=f(H) if (!shcurve || shcurve->isIdentity()) { if (shcurve) { delete shcurve; shcurve = nullptr; } } else { lhutili = true; } bool higplus = false ; int moderetinex = 2; // default to 2 ( deh.retinexMethod == "high" ) if(deh.retinexMethod == "highliplus") { higplus = true; moderetinex = 3; } else if (deh.retinexMethod == "uni") { moderetinex = 0; } else if (deh.retinexMethod == "low") { moderetinex = 1; } else { /*if (deh.retinexMethod == "highli") */ moderetinex = 3; } constexpr float aahi = 49.f / 99.f; ////reduce sensibility 50% constexpr float bbhi = 1.f - aahi; for(int it = 1; it < iter + 1; it++) { //iter nb max of iterations float high = bbhi + aahi * (float) deh.highl; float grad = 1.f; float sc = scal; if(gradient == 0) { grad = 1.f; sc = 3.f; } else if(gradient == 1) { grad = 0.25f * it + 0.75f; sc = -0.5f * it + 4.5f; } else if(gradient == 2) { grad = 0.5f * it + 0.5f; sc = -0.75f * it + 5.75f; } else if(gradient == 3) { grad = 0.666f * it + 0.333f; sc = -0.75f * it + 5.75f; } else if(gradient == 4) { grad = 0.8f * it + 0.2f; sc = -0.75f * it + 5.75f; } else if(gradient == 5) { if(moderetinex != 3) { grad = 2.5f * it - 1.5f; } else { float aa = (11.f * high - 1.f) / 4.f; float bb = 1.f - aa; grad = aa * it + bb; } sc = -0.75f * it + 5.75f; } else if(gradient == 6) { if(moderetinex != 3) { grad = 5.f * it - 4.f; } else { float aa = (21.f * high - 1.f) / 4.f; float bb = 1.f - aa; grad = aa * it + bb; } sc = -0.75f * it + 5.75f; } else if(gradient == -1) { grad = -0.125f * it + 1.125f; sc = 3.f; } if(iter == 1) { sc = scal; } else { //adjust sc in function of choice of scale by user if iterations if(scal < 3) { sc -= 1; if(sc < 1.f) {//avoid 0 sc = 1.f; } } if(scal > 4) { sc += 1; } } float varx = vart; float limdx = limD; float ilimdx = ilimD; if(gradvart != 0) { if(gradvart == 1) { varx = vart * (-0.125f * it + 1.125f); limdx = limD * (-0.125f * it + 1.125f); ilimdx = 1.f / limdx; } else if(gradvart == 2) { varx = vart * (-0.2f * it + 1.2f); limdx = limD * (-0.2f * it + 1.2f); ilimdx = 1.f / limdx; } else if(gradvart == -1) { varx = vart * (0.125f * it + 0.875f); limdx = limD * (0.125f * it + 0.875f); ilimdx = 1.f / limdx; } else if(gradvart == -2) { varx = vart * (0.4f * it + 0.6f); limdx = limD * (0.4f * it + 0.6f); ilimdx = 1.f / limdx; } } scal = round(sc); float ks = 1.f; if(gradstr != 0) { if(gradstr == 1) { if(it <= 3) { ks = -0.3f * it + 1.6f; } else { ks = 0.5f; } } else if(gradstr == 2) { if(it <= 3) { ks = -0.6f * it + 2.2f; } else { ks = 0.3f; } } else if(gradstr == -1) { if(it <= 3) { ks = 0.2f * it + 0.6f; } else { ks = 1.2f; } } else if(gradstr == -2) { if(it <= 3) { ks = 0.4f * it + 0.2f; } else { ks = 1.5f; } } } float strengthx = ks * strength; constexpr auto maxRetinexScales = 8; float RetinexScales[maxRetinexScales]; retinex_scales( RetinexScales, scal, moderetinex, nei / grad, high ); float *src[H_L] ALIGNED16; float *srcBuffer = new float[H_L * W_L]; for (int i = 0; i < H_L; i++) { src[i] = &srcBuffer[i * W_L]; } int h_th = 0, s_th = 0; int shHighlights = deh.highlights; int shShadows = deh.shadows; int mapmet = 0; if(deh.mapMethod == "map") { mapmet = 2; } else if(deh.mapMethod == "mapT") { mapmet = 3; } else if(deh.mapMethod == "gaus") { mapmet = 4; } const double shradius = mapmet == 4 ? (double) deh.radius : 40.; int viewmet = 0; if(deh.viewMethod == "mask") { viewmet = 1; } else if(deh.viewMethod == "tran") { viewmet = 2; } else if(deh.viewMethod == "tran2") { viewmet = 3; } else if(deh.viewMethod == "unsharp") { viewmet = 4; } #ifdef _OPENMP #pragma omp parallel for #endif for (int i = 0; i < H_L; i++) for (int j = 0; j < W_L; j++) { src[i][j] = luminance[i][j] + eps; luminance[i][j] = 0.f; } float *out[H_L] ALIGNED16; float *outBuffer = new float[H_L * W_L]; for (int i = 0; i < H_L; i++) { out[i] = &outBuffer[i * W_L]; } if(viewmet == 3 || viewmet == 2) { tranBuffer = new float[H_L * W_L]; for (int i = 0; i < H_L; i++) { tran[i] = &tranBuffer[i * W_L]; } } const float logBetaGain = xlogf(16384.f); float pond = logBetaGain / (float) scal; if(!useHslLin) { pond /= log(elogt); } auto shmap = ((mapmet == 2 || mapmet == 3 || mapmet == 4) && it == 1) ? new SHMap (W_L, H_L) : nullptr; float *buffer = new float[W_L * H_L];; for ( int scale = scal - 1; scale >= 0; scale-- ) { #ifdef _OPENMP #pragma omp parallel #endif { if(scale == scal - 1) { gaussianBlur (src, out, W_L, H_L, RetinexScales[scale], buffer); } else { // reuse result of last iteration // out was modified in last iteration => restore it if((((mapmet == 2 && scale > 1) || mapmet == 3 || mapmet == 4) || (mapmet > 0 && mapcontlutili)) && it == 1) { #ifdef _OPENMP #pragma omp for #endif for (int i = 0; i < H_L; i++) { for (int j = 0; j < W_L; j++) { out[i][j] = buffer[i * W_L + j]; } } } gaussianBlur (out, out, W_L, H_L, sqrtf(SQR(RetinexScales[scale]) - SQR(RetinexScales[scale + 1])), buffer); } if((((mapmet == 2 && scale > 2) || mapmet == 3 || mapmet == 4) || (mapmet > 0 && mapcontlutili)) && it == 1 && scale > 0) { // out will be modified => store it for use in next iteration. We even don't need a new buffer because 'buffer' is free after gaussianBlur :) #ifdef _OPENMP #pragma omp for #endif for (int i = 0; i < H_L; i++) { for (int j = 0; j < W_L; j++) { buffer[i * W_L + j] = out[i][j]; } } } } if(((mapmet == 2 && scale > 2) || mapmet == 3 || mapmet == 4) && it == 1) { shmap->updateL (out, shradius, true, 1); h_th = shmap->max_f - deh.htonalwidth * (shmap->max_f - shmap->avg) / 100; s_th = deh.stonalwidth * (shmap->avg - shmap->min_f) / 100; } #ifdef __SSE2__ vfloat pondv = F2V(pond); vfloat limMinv = F2V(ilimdx); vfloat limMaxv = F2V(limdx); #endif if(mapmet > 0 && mapcontlutili && it == 1) { // TODO: When rgbcurvespeedup branch is merged into master we can simplify the code by // 1) in rawimagesource.retinexPrepareCurves() insert // mapcurve *= 0.5f; // after // CurveFactory::mapcurve (mapcontlutili, retinexParams.mapcurve, mapcurve, 1, lhist16RETI, histLRETI); // 2) remove the division by 2.f from the code 7 lines below this line #ifdef _OPENMP #pragma omp parallel for #endif for (int i = 0; i < H_L; i++) { for (int j = 0; j < W_L; j++) { out[i][j] = mapcurve[2.f * out[i][j]] / 2.f; } } } if(((mapmet == 2 && scale > 2) || mapmet == 3 || mapmet == 4) && it == 1) { float hWeight = (100.f - shHighlights) / 100.f; float sWeight = (100.f - shShadows) / 100.f; #ifdef _OPENMP #pragma omp parallel for schedule(dynamic,16) #endif for (int i = 0; i < H_L; i++) { for (int j = 0; j < W_L; j++) { float mapval = 1.f + shmap->map[i][j]; float factor = 1.f; if (mapval > h_th) { factor = (h_th + hWeight * (mapval - h_th)) / mapval; } else if (mapval < s_th) { factor = (s_th - sWeight * (s_th - mapval)) / mapval; } out[i][j] *= factor; } } } #ifdef _OPENMP #pragma omp parallel for #endif for (int i = 0; i < H_L; i++) { int j = 0; #ifdef __SSE2__ if(useHslLin) { for (; j < W_L - 3; j += 4) { _mm_storeu_ps(&luminance[i][j], LVFU(luminance[i][j]) + pondv * (vclampf(LVFU(src[i][j]) / LVFU(out[i][j]), limMinv, limMaxv) )); } } else { for (; j < W_L - 3; j += 4) { _mm_storeu_ps(&luminance[i][j], LVFU(luminance[i][j]) + pondv * xlogf(vclampf(LVFU(src[i][j]) / LVFU(out[i][j]), limMinv, limMaxv) )); } } #endif if(useHslLin) { for (; j < W_L; j++) { luminance[i][j] += pond * (LIM(src[i][j] / out[i][j], ilimdx, limdx)); } } else { for (; j < W_L; j++) { luminance[i][j] += pond * xlogf(LIM(src[i][j] / out[i][j], ilimdx, limdx)); // /logt ? } } } } if(mapmet > 1) { if(shmap) { delete shmap; } } shmap = nullptr; delete [] buffer; delete [] srcBuffer; float mean = 0.f; float stddv = 0.f; // I call mean_stddv2 instead of mean_stddv ==> logBetaGain mean_stddv2( luminance, mean, stddv, W_L, H_L, maxtr, mintr); //printf("mean=%f std=%f delta=%f maxtr=%f mintr=%f\n", mean, stddv, delta, maxtr, mintr); //mean_stddv( luminance, mean, stddv, W_L, H_L, logBetaGain, maxtr, mintr); if (dehatransmissionCurve && mean != 0.f && stddv != 0.f) { //if curve float asig = 0.166666f / stddv; float bsig = 0.5f - asig * mean; float amax = 0.333333f / (maxtr - mean - stddv); float bmax = 1.f - amax * maxtr; float amin = 0.333333f / (mean - stddv - mintr); float bmin = -amin * mintr; asig *= 500.f; bsig *= 500.f; amax *= 500.f; bmax *= 500.f; amin *= 500.f; bmin *= 500.f; #ifdef _OPENMP #pragma omp parallel #endif { float absciss; #ifdef _OPENMP #pragma omp for schedule(dynamic,16) #endif for (int i = 0; i < H_L; i++ ) for (int j = 0; j < W_L; j++) { //for mintr to maxtr evalate absciss in function of original transmission if (LIKELY(fabsf(luminance[i][j] - mean) < stddv)) { absciss = asig * luminance[i][j] + bsig; } else if (luminance[i][j] >= mean) { absciss = amax * luminance[i][j] + bmax; } else { /*if(luminance[i][j] <= mean - stddv)*/ absciss = amin * luminance[i][j] + bmin; } //TODO : move multiplication by 4.f and subtraction of 1.f inside the curve luminance[i][j] *= (-1.f + 4.f * dehatransmissionCurve[absciss]); //new transmission if(viewmet == 3 || viewmet == 2) { tran[i][j] = luminance[i][j]; } } } // median filter on transmission ==> reduce artifacts if (deh.medianmap && it == 1) { //only one time int wid = W_L; int hei = H_L; float *tmL[hei] ALIGNED16; float *tmLBuffer = new float[wid * hei]; int borderL = 1; for (int i = 0; i < hei; i++) { tmL[i] = &tmLBuffer[i * wid]; } #ifdef _OPENMP #pragma omp parallel for #endif for (int i = borderL; i < hei - borderL; i++) { for (int j = borderL; j < wid - borderL; j++) { tmL[i][j] = median(luminance[i][j], luminance[i - 1][j], luminance[i + 1][j], luminance[i][j + 1], luminance[i][j - 1], luminance[i - 1][j - 1], luminance[i - 1][j + 1], luminance[i + 1][j - 1], luminance[i + 1][j + 1]); //3x3 } } #ifdef _OPENMP #pragma omp parallel for #endif for (int i = borderL; i < hei - borderL; i++ ) { for (int j = borderL; j < wid - borderL; j++) { luminance[i][j] = tmL[i][j]; } } delete [] tmLBuffer; } // I call mean_stddv2 instead of mean_stddv ==> logBetaGain //mean_stddv( luminance, mean, stddv, W_L, H_L, 1.f, maxtr, mintr); mean_stddv2( luminance, mean, stddv, W_L, H_L, maxtr, mintr); } float epsil = 0.1f; mini = mean - varx * stddv; if (mini < mintr) { mini = mintr + epsil; } maxi = mean + varx * stddv; if (maxi > maxtr) { maxi = maxtr - epsil; } float delta = maxi - mini; //printf("maxi=%f mini=%f mean=%f std=%f delta=%f maxtr=%f mintr=%f\n", maxi, mini, mean, stddv, delta, maxtr, mintr); if ( !delta ) { delta = 1.0f; } float cdfactor = 32768.f / delta; maxCD = -9999999.f; minCD = 9999999.f; // coeff for auto "transmission" with 2 sigma #95% data float aza = 16300.f / (2.f * stddv); float azb = -aza * (mean - 2.f * stddv); float bza = 16300.f / (2.f * stddv); float bzb = 16300.f - bza * (mean); //prepare work for curve gain #ifdef _OPENMP #pragma omp parallel for #endif for (int i = 0; i < H_L; i++) { for (int j = 0; j < W_L; j++) { luminance[i][j] = luminance[i][j] - mini; } } mean = 0.f; stddv = 0.f; // I call mean_stddv2 instead of mean_stddv ==> logBetaGain mean_stddv2( luminance, mean, stddv, W_L, H_L, maxtr, mintr); float asig = 0.f, bsig = 0.f, amax = 0.f, bmax = 0.f, amin = 0.f, bmin = 0.f; if (dehagaintransmissionCurve && mean != 0.f && stddv != 0.f) { //if curve asig = 0.166666f / stddv; bsig = 0.5f - asig * mean; amax = 0.333333f / (maxtr - mean - stddv); bmax = 1.f - amax * maxtr; amin = 0.333333f / (mean - stddv - mintr); bmin = -amin * mintr; asig *= 500.f; bsig *= 500.f; amax *= 500.f; bmax *= 500.f; amin *= 500.f; bmin *= 500.f; } #ifdef _OPENMP #pragma omp parallel #endif { float cdmax = -999999.f, cdmin = 999999.f; #ifdef _OPENMP #pragma omp for schedule(dynamic,16) nowait #endif for ( int i = 0; i < H_L; i ++ ) for (int j = 0; j < W_L; j++) { float gan; if (dehagaintransmissionCurve && mean != 0.f && stddv != 0.f) { float absciss; if (LIKELY(fabsf(luminance[i][j] - mean) < stddv)) { absciss = asig * luminance[i][j] + bsig; } else if (luminance[i][j] >= mean) { absciss = amax * luminance[i][j] + bmax; } else { /*if(luminance[i][j] <= mean - stddv)*/ absciss = amin * luminance[i][j] + bmin; } // float cd = cdfactor * ( luminance[i][j] - mini ) + offse; // TODO : move multiplication by 2.f inside the curve gan = 2.f * (dehagaintransmissionCurve[absciss]); //new gain function transmission } else { gan = 0.5f; } float cd = gan * cdfactor * ( luminance[i][j] ) + offse; cdmax = cd > cdmax ? cd : cdmax; cdmin = cd < cdmin ? cd : cdmin; float str = strengthx; if(lhutili && it == 1) { // S=f(H) { float HH = exLuminance[i][j]; float valparam; if(useHsl || useHslLin) { valparam = float((shcurve->getVal(HH) - 0.5f)); } else { valparam = float((shcurve->getVal(Color::huelab_to_huehsv2(HH)) - 0.5f)); } str *= (1.f + 2.f * valparam); } } if(higplus && exLuminance[i][j] > 65535.f * hig) { str *= hig; } if(viewmet == 0) { luminance[i][j] = intp(str, clipretinex( cd, 0.f, 32768.f ), originalLuminance[i][j]); } else if(viewmet == 1) { luminance[i][j] = out[i][j]; } else if(viewmet == 4) { luminance[i][j] = originalLuminance[i][j] + str * (originalLuminance[i][j] - out[i][j]);//unsharp } else if(viewmet == 2) { if(tran[i][j] <= mean) { luminance[i][j] = azb + aza * tran[i][j]; //auto values } else { luminance[i][j] = bzb + bza * tran[i][j]; } } else { /*if(viewmet == 3) */ luminance[i][j] = 1000.f + tran[i][j] * 700.f; //arbitrary values to help display log values which are between -20 to + 30 - usage values -4 + 5 } } #ifdef _OPENMP #pragma omp critical #endif { maxCD = maxCD > cdmax ? maxCD : cdmax; minCD = minCD < cdmin ? minCD : cdmin; } } delete [] outBuffer; outBuffer = nullptr; //printf("cdmin=%f cdmax=%f\n",minCD, maxCD); Tmean = mean; Tsigma = stddv; Tmin = mintr; Tmax = maxtr; if (shcurve) { delete shcurve; shcurve = nullptr; } } if(tranBuffer) { delete [] tranBuffer; } } } }