//////////////////////////////////////////////////////////////// // // CFA line denoise by DCT filtering // // copyright (c) 2008-2010 Emil Martinec // parallelized 2013 by Ingo Weyrich // // code dated: June 7, 2010 // // cfa_linedn_RT.cc 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. // // This program 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 this program. If not, see . // //////////////////////////////////////////////////////////////// #include #include "rawimagesource.h" #include "rt_math.h" #define TS 224 // Tile size of 224 instead of 512 speeds up processing #define CLASS // %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% using namespace std; using namespace rtengine; // %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% void RawImageSource::CLASS cfa_linedn(float noise, bool horizontal, bool vertical, const CFALineDenoiseRowBlender &rowblender) { // local variables int height = H, width = W; const float clip_pt = 0.8 * initialGain * 65535.0; const float eps = 1e-5; //tolerance to avoid dividing by zero const float gauss[5] = {0.20416368871516755, 0.18017382291138087, 0.1238315368057753, 0.0662822452863612, 0.02763055063889883}; const float rolloff[8] = {0, 0.135335, 0.249352, 0.411112, 0.606531, 0.800737, 0.945959, 1}; //gaussian with sigma=3 const float window[8] = {0, .25, .75, 1, 1, .75, .25, 0}; //sine squared // %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% double progress = 0.0; if (plistener) { plistener->setProgressStr("PROGRESSBAR_LINEDENOISE"); plistener->setProgress(progress); } // %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% float noisevar = SQR(3 * noise * 65535); // _noise_ (as a fraction of saturation) is input to the algorithm float noisevarm4 = 4.0f * noisevar; float* RawDataTmp = (float*)malloc(static_cast(width) * height * sizeof(float)); #ifdef _OPENMP #pragma omp parallel #endif { // allocate memory and assure the arrays don't have same 64 byte boundary to avoid L1 conflict misses float *cfain = (float*)malloc(3 * TS * TS * sizeof(float) + 2 * 16 * sizeof(float)); float *cfadiff = (cfain + (1 * TS * TS) + 1 * 16); float *cfadn = (cfain + (2 * TS * TS) + 2 * 16); float cfablur[TS]; float linehvar[4], linevvar[4], noisefactor[4][8][2], coeffsq; float dctblock[4][8][8]; #ifdef _OPENMP #pragma omp for #endif for(int i = 0; i < height; i++) for(int j = 0; j < width; j++) { RawDataTmp[i * width + j] = rawData[i][j]; } // Main algorithm: Tile loop #ifdef _OPENMP #pragma omp for schedule(dynamic) collapse(2) #endif for (int top = 0; top < height - 16; top += TS - 32) for (int left = 0; left < width - 16; left += TS - 32) { int bottom = min(top + TS, height); int right = min(left + TS, width); int numrows = bottom - top; int numcols = right - left; int indx1; // load CFA data; data should be in linear gamma space, before white balance multipliers are applied for (int rr = top; rr < top + numrows; rr++) for (int cc = left, indx = (rr - top) * TS; cc < left + numcols; cc++, indx++) { cfain[indx] = rawData[rr][cc]; } //pad the block to a multiple of 16 on both sides if (numcols < TS) { indx1 = numcols % 16; for (int i = 0; i < (16 - indx1); i++) for (int rr = 0; rr < numrows; rr++) { cfain[(rr)*TS + numcols + i] = cfain[(rr) * TS + numcols - i - 1]; } numcols += 16 - indx1; } if (numrows < TS) { indx1 = numrows % 16; for (int i = 0; i < (16 - indx1); i++) for (int cc = 0; cc < numcols; cc++) { cfain[(numrows + i)*TS + cc] = cfain[(numrows - i - 1) * TS + cc]; } numrows += 16 - indx1; } //The cleaning algorithm starts here //gaussian blur of CFA data for (int rr = 8; rr < numrows - 8; rr++) { for (int indx = rr * TS, indxb = 0; indx < rr * TS + numcols; indx++, indxb++) { cfablur[indxb] = gauss[0] * cfain[indx]; for (int i = 1; i < 5; i++) { cfablur[indxb] += gauss[i] * (cfain[indx - (2 * i) * TS] + cfain[indx + (2 * i) * TS]); } } for (int indx = rr * TS + 8, indxb = 8; indx < rr * TS + numcols - 8; indx++, indxb++) { cfadn[indx] = gauss[0] * cfablur[indxb]; for (int i = 1; i < 5; i++) { cfadn[indx] += gauss[i] * (cfablur[indxb - 2 * i] + cfablur[indxb + 2 * i]); } cfadiff[indx] = cfain[indx] - cfadn[indx]; // hipass cfa data } } //begin block DCT for (int rr = 8; rr < numrows - 22; rr += 8) // (rr,cc) shift by 8 to overlap blocks for (int cc = 8; cc < numcols - 22; cc += 8) { for (int ey = 0; ey < 2; ey++) // (ex,ey) specify RGGB subarray for (int ex = 0; ex < 2; ex++) { //grab an 8x8 block of a given RGGB channel for (int i = 0; i < 8; i++) for (int j = 0; j < 8; j++) { dctblock[2 * ey + ex][i][j] = cfadiff[(rr + 2 * i + ey) * TS + cc + 2 * j + ex]; } ddct8x8s(-1, dctblock[2 * ey + ex]); //forward DCT } for (int ey = 0; ey < 2; ey++) // (ex,ey) specify RGGB subarray for (int ex = 0; ex < 2; ex++) { linehvar[2 * ey + ex] = linevvar[2 * ey + ex] = 0; for (int i = 4; i < 8; i++) { linehvar[2 * ey + ex] += SQR(dctblock[2 * ey + ex][0][i]); linevvar[2 * ey + ex] += SQR(dctblock[2 * ey + ex][i][0]); } //Wiener filter for line denoising; roll off low frequencies for (int i = 1; i < 8; i++) { coeffsq = SQR(dctblock[2 * ey + ex][i][0]); //vertical noisefactor[2 * ey + ex][i][0] = coeffsq / (coeffsq + rolloff[i] * noisevar + eps); coeffsq = SQR(dctblock[2 * ey + ex][0][i]); //horizontal noisefactor[2 * ey + ex][i][1] = coeffsq / (coeffsq + rolloff[i] * noisevar + eps); // noisefactor labels are [RGGB subarray][row/col position][0=vert,1=hor] } } //horizontal lines if (horizontal && noisevarm4 > (linehvar[0] + linehvar[1])) { //horizontal lines for (int i = 1; i < 8; i++) { dctblock[0][0][i] *= 0.5f * (noisefactor[0][i][1] + noisefactor[1][i][1]); //or should we use MIN??? dctblock[1][0][i] *= 0.5f * (noisefactor[0][i][1] + noisefactor[1][i][1]); //or should we use MIN??? } } if (horizontal && noisevarm4 > (linehvar[2] + linehvar[3])) { //horizontal lines for (int i = 1; i < 8; i++) { dctblock[2][0][i] *= 0.5f * (noisefactor[2][i][1] + noisefactor[3][i][1]); //or should we use MIN??? dctblock[3][0][i] *= 0.5f * (noisefactor[2][i][1] + noisefactor[3][i][1]); //or should we use MIN??? } } //vertical lines if (vertical && noisevarm4 > (linevvar[0] + linevvar[2])) { //vertical lines for (int i = 1; i < 8; i++) { dctblock[0][i][0] *= 0.5f * (noisefactor[0][i][0] + noisefactor[2][i][0]); //or should we use MIN??? dctblock[2][i][0] *= 0.5f * (noisefactor[0][i][0] + noisefactor[2][i][0]); //or should we use MIN??? } } if (vertical && noisevarm4 > (linevvar[1] + linevvar[3])) { //vertical lines for (int i = 1; i < 8; i++) { dctblock[1][i][0] *= 0.5f * (noisefactor[1][i][0] + noisefactor[3][i][0]); //or should we use MIN??? dctblock[3][i][0] *= 0.5f * (noisefactor[1][i][0] + noisefactor[3][i][0]); //or should we use MIN??? } } for (int ey = 0; ey < 2; ey++) // (ex,ey) specify RGGB subarray for (int ex = 0; ex < 2; ex++) { ddct8x8s(1, dctblock[2 * ey + ex]); //inverse DCT //multiply by window fn and add to output (cfadn) for (int i = 0; i < 8; i++) for (int j = 0; j < 8; j++) { cfadn[(rr + 2 * i + ey)*TS + cc + 2 * j + ex] += window[i] * window[j] * dctblock[2 * ey + ex][i][j]; } } } // %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% // copy smoothed results to temporary buffer for (int rr = 16; rr < numrows - 16; rr++) { int row = rr + top; for (int col = 16 + left, indx = rr * TS + 16; indx < rr * TS + numcols - 16; indx++, col++) { if (rawData[row][col] < clip_pt && cfadn[indx] < clip_pt) { RawDataTmp[row * width + col] = CLIP(cfadn[indx]); } } } if(plistener) { progress += (double)((TS - 32) * (TS - 32)) / (height * width); if (progress > 1.0) { progress = 1.0; } plistener->setProgress(progress); } } // clean up free(cfain); // copy temporary buffer back to image matrix #ifdef _OPENMP #pragma omp for schedule(dynamic,16) #endif for(int i = 0; i < height; i++) { float f = rowblender(i); if (f > 0.f) { float f2 = 1.f - f; for(int j = 0; j < width; j++) { rawData[i][j] = f * RawDataTmp[i * width + j] + f2 * rawData[i][j]; } } } } // end of parallel processing free(RawDataTmp); } #undef TS //%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% /* Discrete Cosine Transform Code Copyright(C) 1997 Takuya OOURA (email: ooura@mmm.t.u-tokyo.ac.jp). You may use, copy, modify this code for any purpose and without fee. You may distribute this ORIGINAL package. */ /* Short Discrete Cosine Transform data length :8x8 method :row-column, radix 4 FFT functions ddct8x8s : 8x8 DCT function prototypes void ddct8x8s(int isgn, float **a); */ /* -------- 8x8 DCT (Discrete Cosine Transform) / Inverse of DCT -------- [definition] Normalized 8x8 IDCT C[k1][k2] = (1/4) * sum_j1=0^7 sum_j2=0^7 a[j1][j2] * s[j1] * s[j2] * cos(pi*j1*(k1+1/2)/8) * cos(pi*j2*(k2+1/2)/8), 0<=k1<8, 0<=k2<8 (s[0] = 1/sqrt(2), s[j] = 1, j > 0) Normalized 8x8 DCT C[k1][k2] = (1/4) * s[k1] * s[k2] * sum_j1=0^7 sum_j2=0^7 a[j1][j2] * cos(pi*(j1+1/2)*k1/8) * cos(pi*(j2+1/2)*k2/8), 0<=k1<8, 0<=k2<8 (s[0] = 1/sqrt(2), s[j] = 1, j > 0) [usage] ddct8x8s(1, a); ddct8x8s(-1, a); [parameters] a[0...7][0...7] :input/output data (double **) output data a[k1][k2] = C[k1][k2], 0<=k1<8, 0<=k2<8 */ /* Cn_kR = sqrt(2.0/n) * cos(pi/2*k/n) */ /* Cn_kI = sqrt(2.0/n) * sin(pi/2*k/n) */ /* Wn_kR = cos(pi/2*k/n) */ /* Wn_kI = sin(pi/2*k/n) */ #define C8_1R 0.49039264020161522456f #define C8_1I 0.09754516100806413392f #define C8_2R 0.46193976625564337806f #define C8_2I 0.19134171618254488586f #define C8_3R 0.41573480615127261854f #define C8_3I 0.27778511650980111237f #define C8_4R 0.35355339059327376220f #define W8_4R 0.70710678118654752440f void RawImageSource::ddct8x8s(int isgn, float a[8][8]) { int j; float x0r, x0i, x1r, x1i, x2r, x2i, x3r, x3i; float xr, xi; if (isgn < 0) { for (j = 0; j <= 7; j++) { x0r = a[0][j] + a[7][j]; x1r = a[0][j] - a[7][j]; x0i = a[2][j] + a[5][j]; x1i = a[2][j] - a[5][j]; x2r = a[4][j] + a[3][j]; x3r = a[4][j] - a[3][j]; x2i = a[6][j] + a[1][j]; x3i = a[6][j] - a[1][j]; xr = x0r + x2r; xi = x0i + x2i; a[0][j] = C8_4R * (xr + xi); a[4][j] = C8_4R * (xr - xi); xr = x0r - x2r; xi = x0i - x2i; a[2][j] = C8_2R * xr - C8_2I * xi; a[6][j] = C8_2R * xi + C8_2I * xr; xr = W8_4R * (x1i - x3i); x1i = W8_4R * (x1i + x3i); x3i = x1i - x3r; x1i += x3r; x3r = x1r - xr; x1r += xr; a[1][j] = C8_1R * x1r - C8_1I * x1i; a[7][j] = C8_1R * x1i + C8_1I * x1r; a[3][j] = C8_3R * x3r - C8_3I * x3i; a[5][j] = C8_3R * x3i + C8_3I * x3r; } for (j = 0; j <= 7; j++) { x0r = a[j][0] + a[j][7]; x1r = a[j][0] - a[j][7]; x0i = a[j][2] + a[j][5]; x1i = a[j][2] - a[j][5]; x2r = a[j][4] + a[j][3]; x3r = a[j][4] - a[j][3]; x2i = a[j][6] + a[j][1]; x3i = a[j][6] - a[j][1]; xr = x0r + x2r; xi = x0i + x2i; a[j][0] = C8_4R * (xr + xi); a[j][4] = C8_4R * (xr - xi); xr = x0r - x2r; xi = x0i - x2i; a[j][2] = C8_2R * xr - C8_2I * xi; a[j][6] = C8_2R * xi + C8_2I * xr; xr = W8_4R * (x1i - x3i); x1i = W8_4R * (x1i + x3i); x3i = x1i - x3r; x1i += x3r; x3r = x1r - xr; x1r += xr; a[j][1] = C8_1R * x1r - C8_1I * x1i; a[j][7] = C8_1R * x1i + C8_1I * x1r; a[j][3] = C8_3R * x3r - C8_3I * x3i; a[j][5] = C8_3R * x3i + C8_3I * x3r; } } else { for (j = 0; j <= 7; j++) { x1r = C8_1R * a[1][j] + C8_1I * a[7][j]; x1i = C8_1R * a[7][j] - C8_1I * a[1][j]; x3r = C8_3R * a[3][j] + C8_3I * a[5][j]; x3i = C8_3R * a[5][j] - C8_3I * a[3][j]; xr = x1r - x3r; xi = x1i + x3i; x1r += x3r; x3i -= x1i; x1i = W8_4R * (xr + xi); x3r = W8_4R * (xr - xi); xr = C8_2R * a[2][j] + C8_2I * a[6][j]; xi = C8_2R * a[6][j] - C8_2I * a[2][j]; x0r = C8_4R * (a[0][j] + a[4][j]); x0i = C8_4R * (a[0][j] - a[4][j]); x2r = x0r - xr; x2i = x0i - xi; x0r += xr; x0i += xi; a[0][j] = x0r + x1r; a[7][j] = x0r - x1r; a[2][j] = x0i + x1i; a[5][j] = x0i - x1i; a[4][j] = x2r - x3i; a[3][j] = x2r + x3i; a[6][j] = x2i - x3r; a[1][j] = x2i + x3r; } for (j = 0; j <= 7; j++) { x1r = C8_1R * a[j][1] + C8_1I * a[j][7]; x1i = C8_1R * a[j][7] - C8_1I * a[j][1]; x3r = C8_3R * a[j][3] + C8_3I * a[j][5]; x3i = C8_3R * a[j][5] - C8_3I * a[j][3]; xr = x1r - x3r; xi = x1i + x3i; x1r += x3r; x3i -= x1i; x1i = W8_4R * (xr + xi); x3r = W8_4R * (xr - xi); xr = C8_2R * a[j][2] + C8_2I * a[j][6]; xi = C8_2R * a[j][6] - C8_2I * a[j][2]; x0r = C8_4R * (a[j][0] + a[j][4]); x0i = C8_4R * (a[j][0] - a[j][4]); x2r = x0r - xr; x2i = x0i - xi; x0r += xr; x0i += xi; a[j][0] = x0r + x1r; a[j][7] = x0r - x1r; a[j][2] = x0i + x1i; a[j][5] = x0i - x1i; a[j][4] = x2r - x3i; a[j][3] = x2r + x3i; a[j][6] = x2i - x3r; a[j][1] = x2i + x3r; } } }