8b2eac9a3d
The pipette part is already working quite nice but need to be finished. The widgets part needs more work...
428 lines
14 KiB
C++
428 lines
14 KiB
C++
////////////////////////////////////////////////////////////////
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//
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// CFA line denoise by DCT filtering
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//
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// copyright (c) 2008-2010 Emil Martinec <ejmartin@uchicago.edu>
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// parallelized 2013 by Ingo Weyrich
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//
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// code dated: June 7, 2010
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//
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// cfa_linedn_RT.cc is free software: you can redistribute it and/or modify
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// it under the terms of the GNU General Public License as published by
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// the Free Software Foundation, either version 3 of the License, or
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// (at your option) any later version.
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//
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// This program is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU General Public License
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// along with this program. If not, see <http://www.gnu.org/licenses/>.
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//
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////////////////////////////////////////////////////////////////
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#include <cmath>
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#include "rtengine.h"
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#include "rawimagesource.h"
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#include "rt_math.h"
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#define TS 224 // Tile size of 224 instead of 512 speeds up processing
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#define CLASS
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// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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using namespace std;
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using namespace rtengine;
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// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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void RawImageSource::CLASS cfa_linedn(float noise)
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{
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// local variables
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int height=H, width=W;
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const float clip_pt = 0.8*initialGain* 65535.0;
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float eps=1e-5; //tolerance to avoid dividing by zero
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const float gauss[5] = {0.20416368871516755, 0.18017382291138087, 0.1238315368057753, 0.0662822452863612, 0.02763055063889883};
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const float rolloff[8] = {0, 0.135335, 0.249352, 0.411112, 0.606531, 0.800737, 0.945959, 1}; //gaussian with sigma=3
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const float window[8] = {0, .25, .75, 1, 1, .75, .25, 0}; //sine squared
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// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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if (plistener) {
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plistener->setProgressStr ("Line Denoise...");
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plistener->setProgress (0.0);
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}
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// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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float noisevar=SQR(3*noise*65535); // _noise_ (as a fraction of saturation) is input to the algorithm
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float noisevarm4 = 4.0f * noisevar;
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volatile double progress = 0.0;
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float* RawDataTmp = (float*)malloc( width*height*sizeof(float));
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#pragma omp parallel
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{
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// allocate memory and assure the arrays don't have same 64 byte boundary to avoid L1 conflict misses
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char *buffer = (char*)malloc(4 * TS * TS * sizeof(float)+ 3*64);
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float *cfain = (float*)(buffer);
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float *cfablur =(float*)(buffer+(TS*TS*sizeof(float))+ 1 * 64);
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float *cfadiff =(float*)(buffer+(2*TS*TS*sizeof(float))+ 2 * 64);
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float *cfadn =(float*)(buffer+(3*TS*TS*sizeof(float))+ 3 * 64);
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float linehvar[4], linevvar[4], noisefactor[4][8][2], coeffsq;
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float dctblock[4][8][8];
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#pragma omp for
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for(int i=0;i<height;i++)
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for(int j=0;j<width;j++)
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RawDataTmp[i*width+j] = rawData[i][j];
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// Main algorithm: Tile loop
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#pragma omp for schedule(dynamic) collapse(2)
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for (int top=0; top < height-16; top += TS-32)
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for (int left=0; left < width-16; left += TS-32) {
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int bottom = min(top+TS,height);
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int right = min(left+TS, width);
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int numrows = bottom - top;
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int numcols = right - left;
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int indx1;
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// load CFA data; data should be in linear gamma space, before white balance multipliers are applied
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for (int rr=top; rr < top+numrows; rr++)
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for (int cc=left, indx=(rr-top)*TS; cc < left+numcols; cc++, indx++) {
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cfain[indx] = rawData[rr][cc];
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}
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//pad the block to a multiple of 16 on both sides
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if (numcols < TS) {
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indx1=numcols % 16;
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for (int i=0; i<(16-indx1); i++)
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for (int rr=0; rr<numrows; rr++)
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cfain[(rr)*TS+numcols+i]=cfain[(rr)*TS+numcols-i-1];
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numcols += 16-indx1;
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}
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if (numrows < TS) {
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indx1=numrows % 16;
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for (int i=0; i<(16-indx1); i++)
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for (int cc=0; cc<numcols; cc++)
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cfain[(numrows+i)*TS+cc]=cfain[(numrows-i-1)*TS+cc];
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numrows += 16-indx1;
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}
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//The cleaning algorithm starts here
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//gaussian blur of CFA data
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for (int rr=8; rr < numrows-8; rr++){
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for (int indx=rr*TS; indx < rr*TS+numcols; indx++) {
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cfablur[indx]=gauss[0]*cfain[indx];
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for (int i=1; i<5; i++) {
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cfablur[indx] += gauss[i]*(cfain[indx-(2*i)*TS]+cfain[indx+(2*i)*TS]);
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}
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}
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for (int indx=rr*TS+8; indx < rr*TS+numcols-8; indx++) {
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cfadn[indx] = gauss[0]*cfablur[indx];
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for (int i=1; i<5; i++) {
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cfadn[indx] += gauss[i]*(cfablur[indx-2*i]+cfablur[indx+2*i]);
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}
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cfadiff[indx]=cfain[indx]-cfadn[indx]; // hipass cfa data
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}
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}
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//begin block DCT
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for (int rr=8; rr < numrows-22; rr+=8) // (rr,cc) shift by 8 to overlap blocks
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for (int cc=8; cc < numcols-22; cc+=8) {
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for (int ey=0; ey<2; ey++) // (ex,ey) specify RGGB subarray
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for (int ex=0; ex<2; ex++) {
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//grab an 8x8 block of a given RGGB channel
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for (int i=0; i<8; i++)
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for (int j=0; j<8; j++) {
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dctblock[2*ey+ex][i][j]=cfadiff[(rr+2*i+ey)*TS+cc+2*j+ex];
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}
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ddct8x8s(-1, dctblock[2*ey+ex]); //forward DCT
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}
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for (int ey=0; ey<2; ey++) // (ex,ey) specify RGGB subarray
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for (int ex=0; ex<2; ex++) {
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linehvar[2*ey+ex]=linevvar[2*ey+ex]=0;
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for (int i=4; i<8; i++) {
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linehvar[2*ey+ex] += SQR(dctblock[2*ey+ex][0][i]);
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linevvar[2*ey+ex] += SQR(dctblock[2*ey+ex][i][0]);
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}
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//Wiener filter for line denoising; roll off low frequencies
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for (int i=1; i<8; i++) {
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coeffsq = SQR(dctblock[2*ey+ex][i][0]);//vertical
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noisefactor[2*ey+ex][i][0] = coeffsq/(coeffsq+rolloff[i]*noisevar+eps);
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coeffsq = SQR(dctblock[2*ey+ex][0][i]);//horizontal
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noisefactor[2*ey+ex][i][1] = coeffsq/(coeffsq+rolloff[i]*noisevar+eps);
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// noisefactor labels are [RGGB subarray][row/col position][0=vert,1=hor]
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}
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}
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//horizontal lines
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if (noisevarm4>(linehvar[0]+linehvar[1])) {//horizontal lines
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for (int i=1; i<8; i++) {
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dctblock[0][0][i] *= 0.5f*(noisefactor[0][i][1]+noisefactor[1][i][1]);//or should we use MIN???
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dctblock[1][0][i] *= 0.5f*(noisefactor[0][i][1]+noisefactor[1][i][1]);//or should we use MIN???
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}
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}
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if (noisevarm4>(linehvar[2]+linehvar[3])) {//horizontal lines
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for (int i=1; i<8; i++) {
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dctblock[2][0][i] *= 0.5f*(noisefactor[2][i][1]+noisefactor[3][i][1]);//or should we use MIN???
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dctblock[3][0][i] *= 0.5f*(noisefactor[2][i][1]+noisefactor[3][i][1]);//or should we use MIN???
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}
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}
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//vertical lines
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if (noisevarm4>(linevvar[0]+linevvar[2])) {//vertical lines
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for (int i=1; i<8; i++) {
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dctblock[0][i][0] *= 0.5f*(noisefactor[0][i][0]+noisefactor[2][i][0]);//or should we use MIN???
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dctblock[2][i][0] *= 0.5f*(noisefactor[0][i][0]+noisefactor[2][i][0]);//or should we use MIN???
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}
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}
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if (noisevarm4>(linevvar[1]+linevvar[3])) {//vertical lines
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for (int i=1; i<8; i++) {
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dctblock[1][i][0] *= 0.5f*(noisefactor[1][i][0]+noisefactor[3][i][0]);//or should we use MIN???
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dctblock[3][i][0] *= 0.5f*(noisefactor[1][i][0]+noisefactor[3][i][0]);//or should we use MIN???
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}
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}
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for (int ey=0; ey<2; ey++) // (ex,ey) specify RGGB subarray
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for (int ex=0; ex<2; ex++) {
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ddct8x8s(1, dctblock[2*ey+ex]); //inverse DCT
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//multiply by window fn and add to output (cfadn)
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for (int i=0; i<8; i++)
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for (int j=0; j<8; j++) {
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cfadn[(rr+2*i+ey)*TS+cc+2*j+ex] += window[i]*window[j]*dctblock[2*ey+ex][i][j];
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}
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}
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}
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// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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// copy smoothed results to temporary buffer
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for (int rr=16; rr < numrows-16; rr++) {
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int row = rr + top;
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for (int col=16+left, indx=rr*TS+16; indx < rr*TS+numcols-16; indx++, col++) {
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if (rawData[row][col]<clip_pt && cfadn[indx]<clip_pt)
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RawDataTmp[row*width+col] = CLIP((int)(cfadn[indx]+ 0.5f));
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}
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}
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if(plistener) {
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progress+=(double)((TS-32)*(TS-32))/(height*width);
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if (progress>1.0)
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{
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progress=1.0;
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}
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plistener->setProgress(progress);
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}
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}
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// clean up
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free(buffer);
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// copy temporary buffer back to image matrix
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#pragma omp for
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for(int i=0;i<height;i++)
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for(int j=0;j<width;j++)
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rawData[i][j] = RawDataTmp[i*width+j];
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} // end of parallel processing
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free(RawDataTmp);
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}
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#undef TS
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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/*
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Discrete Cosine Transform Code
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Copyright(C) 1997 Takuya OOURA (email: ooura@mmm.t.u-tokyo.ac.jp).
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You may use, copy, modify this code for any purpose and
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without fee. You may distribute this ORIGINAL package.
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*/
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/*
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Short Discrete Cosine Transform
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data length :8x8
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method :row-column, radix 4 FFT
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functions
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ddct8x8s : 8x8 DCT
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function prototypes
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void ddct8x8s(int isgn, float **a);
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*/
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/*
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-------- 8x8 DCT (Discrete Cosine Transform) / Inverse of DCT --------
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[definition]
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<case1> Normalized 8x8 IDCT
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C[k1][k2] = (1/4) * sum_j1=0^7 sum_j2=0^7
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a[j1][j2] * s[j1] * s[j2] *
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cos(pi*j1*(k1+1/2)/8) *
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cos(pi*j2*(k2+1/2)/8), 0<=k1<8, 0<=k2<8
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(s[0] = 1/sqrt(2), s[j] = 1, j > 0)
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<case2> Normalized 8x8 DCT
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C[k1][k2] = (1/4) * s[k1] * s[k2] * sum_j1=0^7 sum_j2=0^7
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a[j1][j2] *
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cos(pi*(j1+1/2)*k1/8) *
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cos(pi*(j2+1/2)*k2/8), 0<=k1<8, 0<=k2<8
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(s[0] = 1/sqrt(2), s[j] = 1, j > 0)
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[usage]
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<case1>
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ddct8x8s(1, a);
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<case2>
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ddct8x8s(-1, a);
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[parameters]
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a[0...7][0...7] :input/output data (double **)
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output data
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a[k1][k2] = C[k1][k2], 0<=k1<8, 0<=k2<8
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*/
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/* Cn_kR = sqrt(2.0/n) * cos(pi/2*k/n) */
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/* Cn_kI = sqrt(2.0/n) * sin(pi/2*k/n) */
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/* Wn_kR = cos(pi/2*k/n) */
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/* Wn_kI = sin(pi/2*k/n) */
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#define C8_1R 0.49039264020161522456
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#define C8_1I 0.09754516100806413392
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#define C8_2R 0.46193976625564337806
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#define C8_2I 0.19134171618254488586
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#define C8_3R 0.41573480615127261854
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#define C8_3I 0.27778511650980111237
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#define C8_4R 0.35355339059327376220
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#define W8_4R 0.70710678118654752440
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void RawImageSource::ddct8x8s(int isgn, float a[8][8])
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{
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int j;
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float x0r, x0i, x1r, x1i, x2r, x2i, x3r, x3i;
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float xr, xi;
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if (isgn < 0) {
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for (j = 0; j <= 7; j++) {
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x0r = a[0][j] + a[7][j];
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x1r = a[0][j] - a[7][j];
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x0i = a[2][j] + a[5][j];
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x1i = a[2][j] - a[5][j];
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x2r = a[4][j] + a[3][j];
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x3r = a[4][j] - a[3][j];
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x2i = a[6][j] + a[1][j];
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x3i = a[6][j] - a[1][j];
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xr = x0r + x2r;
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xi = x0i + x2i;
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a[0][j] = C8_4R * (xr + xi);
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a[4][j] = C8_4R * (xr - xi);
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xr = x0r - x2r;
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xi = x0i - x2i;
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a[2][j] = C8_2R * xr - C8_2I * xi;
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a[6][j] = C8_2R * xi + C8_2I * xr;
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xr = W8_4R * (x1i - x3i);
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x1i = W8_4R * (x1i + x3i);
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x3i = x1i - x3r;
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x1i += x3r;
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x3r = x1r - xr;
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x1r += xr;
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a[1][j] = C8_1R * x1r - C8_1I * x1i;
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a[7][j] = C8_1R * x1i + C8_1I * x1r;
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a[3][j] = C8_3R * x3r - C8_3I * x3i;
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a[5][j] = C8_3R * x3i + C8_3I * x3r;
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}
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for (j = 0; j <= 7; j++) {
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x0r = a[j][0] + a[j][7];
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x1r = a[j][0] - a[j][7];
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x0i = a[j][2] + a[j][5];
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x1i = a[j][2] - a[j][5];
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x2r = a[j][4] + a[j][3];
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x3r = a[j][4] - a[j][3];
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x2i = a[j][6] + a[j][1];
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x3i = a[j][6] - a[j][1];
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xr = x0r + x2r;
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xi = x0i + x2i;
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a[j][0] = C8_4R * (xr + xi);
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a[j][4] = C8_4R * (xr - xi);
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xr = x0r - x2r;
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xi = x0i - x2i;
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a[j][2] = C8_2R * xr - C8_2I * xi;
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a[j][6] = C8_2R * xi + C8_2I * xr;
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xr = W8_4R * (x1i - x3i);
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x1i = W8_4R * (x1i + x3i);
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x3i = x1i - x3r;
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x1i += x3r;
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x3r = x1r - xr;
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x1r += xr;
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a[j][1] = C8_1R * x1r - C8_1I * x1i;
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a[j][7] = C8_1R * x1i + C8_1I * x1r;
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a[j][3] = C8_3R * x3r - C8_3I * x3i;
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a[j][5] = C8_3R * x3i + C8_3I * x3r;
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}
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} else {
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for (j = 0; j <= 7; j++) {
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x1r = C8_1R * a[1][j] + C8_1I * a[7][j];
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x1i = C8_1R * a[7][j] - C8_1I * a[1][j];
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x3r = C8_3R * a[3][j] + C8_3I * a[5][j];
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x3i = C8_3R * a[5][j] - C8_3I * a[3][j];
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xr = x1r - x3r;
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xi = x1i + x3i;
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x1r += x3r;
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x3i -= x1i;
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x1i = W8_4R * (xr + xi);
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x3r = W8_4R * (xr - xi);
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xr = C8_2R * a[2][j] + C8_2I * a[6][j];
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xi = C8_2R * a[6][j] - C8_2I * a[2][j];
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x0r = C8_4R * (a[0][j] + a[4][j]);
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x0i = C8_4R * (a[0][j] - a[4][j]);
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x2r = x0r - xr;
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x2i = x0i - xi;
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x0r += xr;
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x0i += xi;
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a[0][j] = x0r + x1r;
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a[7][j] = x0r - x1r;
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a[2][j] = x0i + x1i;
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a[5][j] = x0i - x1i;
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a[4][j] = x2r - x3i;
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a[3][j] = x2r + x3i;
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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;
|
|
}
|
|
}
|
|
}
|
|
|