merged 'rcd-demosaic' into 'dev'

This commit is contained in:
Alberto Griggio 2017-12-08 18:53:03 +01:00
commit 503fe902a0
6 changed files with 299 additions and 0 deletions

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@ -1788,6 +1788,7 @@ TP_RAW_PIXELSHIFTSMOOTH_TOOLTIP;Smooth transitions between areas with motion and
TP_RAW_PIXELSHIFTSTDDEVFACTORBLUE;StdDev factor Blue
TP_RAW_PIXELSHIFTSTDDEVFACTORGREEN;StdDev factor Green
TP_RAW_PIXELSHIFTSTDDEVFACTORRED;StdDev factor Red
TP_RAW_RCD;RCD
TP_RAW_SENSOR_BAYER_LABEL;Sensor with Bayer Matrix
TP_RAW_SENSOR_XTRANS_DMETHOD_TOOLTIP;3-pass gives best results (recommended for low ISO images).\n1-pass is almost undistinguishable from 3-pass for high ISO images and is faster.
TP_RAW_SENSOR_XTRANS_LABEL;Sensor with X-Trans Matrix

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@ -3928,6 +3928,299 @@ void RawImageSource::cielab (const float (*rgb)[3], float* l, float* a, float *b
}
}
/**
* RATIO CORRECTED DEMOSAICING
* Luis Sanz Rodriguez (luis.sanz.rodriguez(at)gmail(dot)com)
*
* Release 2.3 @ 171125
*
* Original code from https://github.com/LuisSR/RCD-Demosaicing
* Licensed under the GNU GPL version 3
*/
void RawImageSource::rcd_demosaic()
{
// RT ---------------------------------------------------------------------
if (plistener) {
plistener->setProgressStr(Glib::ustring::compose(M("TP_RAW_DMETHOD_PROGRESSBAR"), "rcd"));
plistener->setProgress(0);
}
int width = W, height = H;
std::vector<float> cfa(width * height);
std::vector<std::array<float, 3>> rgb(width * height);
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int row = 0; row < height; row++) {
for (int col = 0, indx = row * width + col; col < width; col++, indx++) {
int c = FC(row, col);
cfa[indx] = rgb[indx][c] = LIM01(rawData[row][col] / 65535.f);
}
}
if (plistener) {
plistener->setProgress(0.05);
}
// ------------------------------------------------------------------------
/* RT
int row, col, indx, c;
*/
int w1 = width, w2 = 2 * width, w3 = 3 * width, w4 = 4 * width;
//Tolerance to avoid dividing by zero
static const float eps = 1e-5, epssq = 1e-10;
/* RT
//Gradients
float N_Grad, E_Grad, W_Grad, S_Grad, NW_Grad, NE_Grad, SW_Grad, SE_Grad;
//Pixel estimation
float N_Est, E_Est, W_Est, S_Est, NW_Est, NE_Est, SW_Est, SE_Est, V_Est, H_Est, P_Est, Q_Est;
//Directional discrimination
//float V_Stat, H_Stat, P_Stat, Q_Stat;
float VH_Central_Value, VH_Neighbour_Value, PQ_Central_Value, PQ_Neighbour_Value;
*/
float ( *VH_Dir ), ( *PQ_Dir );
//Low pass filter
float ( *lpf );
/**
* STEP 1: Find cardinal and diagonal interpolation directions
*/
VH_Dir = ( float ( * ) ) calloc( width * height, sizeof *VH_Dir ); //merror ( VH_Dir, "rcd_demosaicing_171117()" );
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int row = 4; row < height - 4; row++ ) {
for (int col = 4, indx = row * width + col; col < width - 4; col++, indx++ ) {
//Calculate h/v local discrimination
float V_Stat = max(epssq, - 18.0f * cfa[indx] * cfa[indx - w1] - 18.0f * cfa[indx] * cfa[indx + w1] - 36.0f * cfa[indx] * cfa[indx - w2] - 36.0f * cfa[indx] * cfa[indx + w2] + 18.0f * cfa[indx] * cfa[indx - w3] + 18.0f * cfa[indx] * cfa[indx + w3] - 2.0f * cfa[indx] * cfa[indx - w4] - 2.0f * cfa[indx] * cfa[indx + w4] + 38.0f * cfa[indx] * cfa[indx] - 70.0f * cfa[indx - w1] * cfa[indx + w1] - 12.0f * cfa[indx - w1] * cfa[indx - w2] + 24.0f * cfa[indx - w1] * cfa[indx + w2] - 38.0f * cfa[indx - w1] * cfa[indx - w3] + 16.0f * cfa[indx - w1] * cfa[indx + w3] + 12.0f * cfa[indx - w1] * cfa[indx - w4] - 6.0f * cfa[indx - w1] * cfa[indx + w4] + 46.0f * cfa[indx - w1] * cfa[indx - w1] + 24.0f * cfa[indx + w1] * cfa[indx - w2] - 12.0f * cfa[indx + w1] * cfa[indx + w2] + 16.0f * cfa[indx + w1] * cfa[indx - w3] - 38.0f * cfa[indx + w1] * cfa[indx + w3] - 6.0f * cfa[indx + w1] * cfa[indx - w4] + 12.0f * cfa[indx + w1] * cfa[indx + w4] + 46.0f * cfa[indx + w1] * cfa[indx + w1] + 14.0f * cfa[indx - w2] * cfa[indx + w2] - 12.0f * cfa[indx - w2] * cfa[indx + w3] - 2.0f * cfa[indx - w2] * cfa[indx - w4] + 2.0f * cfa[indx - w2] * cfa[indx + w4] + 11.0f * cfa[indx - w2] * cfa[indx - w2] - 12.0f * cfa[indx + w2] * cfa[indx - w3] + 2.0f * cfa[indx + w2] * cfa[indx - w4] - 2.0f * cfa[indx + w2] * cfa[indx + w4] + 11.0f * cfa[indx + w2] * cfa[indx + w2] + 2.0f * cfa[indx - w3] * cfa[indx + w3] - 6.0f * cfa[indx - w3] * cfa[indx - w4] + 10.0f * cfa[indx - w3] * cfa[indx - w3] - 6.0f * cfa[indx + w3] * cfa[indx + w4] + 10.0f * cfa[indx + w3] * cfa[indx + w3] + 1.0f * cfa[indx - w4] * cfa[indx - w4] + 1.0f * cfa[indx + w4] * cfa[indx + w4]);
float H_Stat = max(epssq, - 18.0f * cfa[indx] * cfa[indx - 1] - 18.0f * cfa[indx] * cfa[indx + 1] - 36.0f * cfa[indx] * cfa[indx - 2] - 36.0f * cfa[indx] * cfa[indx + 2] + 18.0f * cfa[indx] * cfa[indx - 3] + 18.0f * cfa[indx] * cfa[indx + 3] - 2.0f * cfa[indx] * cfa[indx - 4] - 2.0f * cfa[indx] * cfa[indx + 4] + 38.0f * cfa[indx] * cfa[indx] - 70.0f * cfa[indx - 1] * cfa[indx + 1] - 12.0f * cfa[indx - 1] * cfa[indx - 2] + 24.0f * cfa[indx - 1] * cfa[indx + 2] - 38.0f * cfa[indx - 1] * cfa[indx - 3] + 16.0f * cfa[indx - 1] * cfa[indx + 3] + 12.0f * cfa[indx - 1] * cfa[indx - 4] - 6.0f * cfa[indx - 1] * cfa[indx + 4] + 46.0f * cfa[indx - 1] * cfa[indx - 1] + 24.0f * cfa[indx + 1] * cfa[indx - 2] - 12.0f * cfa[indx + 1] * cfa[indx + 2] + 16.0f * cfa[indx + 1] * cfa[indx - 3] - 38.0f * cfa[indx + 1] * cfa[indx + 3] - 6.0f * cfa[indx + 1] * cfa[indx - 4] + 12.0f * cfa[indx + 1] * cfa[indx + 4] + 46.0f * cfa[indx + 1] * cfa[indx + 1] + 14.0f * cfa[indx - 2] * cfa[indx + 2] - 12.0f * cfa[indx - 2] * cfa[indx + 3] - 2.0f * cfa[indx - 2] * cfa[indx - 4] + 2.0f * cfa[indx - 2] * cfa[indx + 4] + 11.0f * cfa[indx - 2] * cfa[indx - 2] - 12.0f * cfa[indx + 2] * cfa[indx - 3] + 2.0f * cfa[indx + 2] * cfa[indx - 4] - 2.0f * cfa[indx + 2] * cfa[indx + 4] + 11.0f * cfa[indx + 2] * cfa[indx + 2] + 2.0f * cfa[indx - 3] * cfa[indx + 3] - 6.0f * cfa[indx - 3] * cfa[indx - 4] + 10.0f * cfa[indx - 3] * cfa[indx - 3] - 6.0f * cfa[indx + 3] * cfa[indx + 4] + 10.0f * cfa[indx + 3] * cfa[indx + 3] + 1.0f * cfa[indx - 4] * cfa[indx - 4] + 1.0f * cfa[indx + 4] * cfa[indx + 4]);
VH_Dir[indx] = V_Stat / (V_Stat + H_Stat);
}
}
// RT ---------------------------------------------------------------------
if (plistener) {
plistener->setProgress(0.2);
}
// -------------------------------------------------------------------------
/**
* STEP 2: Calculate the low pass filter
*/
// Step 2.1: Low pass filter incorporating green, red and blue local samples from the raw data
lpf = ( float ( * ) ) calloc( width * height, sizeof *lpf ); //merror ( lpf, "rcd_demosaicing_171125()" );
#ifdef _OPENMP
#pragma omp parallel for
#endif
for ( int row = 2; row < height - 2; row++ ) {
for ( int col = 2 + (FC( row, 0 ) & 1), indx = row * width + col; col < width - 2; col += 2, indx += 2 ) {
lpf[indx] = 0.25f * cfa[indx] + 0.125f * ( cfa[indx - w1] + cfa[indx + w1] + cfa[indx - 1] + cfa[indx + 1] ) + 0.0625f * ( cfa[indx - w1 - 1] + cfa[indx - w1 + 1] + cfa[indx + w1 - 1] + cfa[indx + w1 + 1] );
}
}
// RT ---------------------------------------------------------------------
if (plistener) {
plistener->setProgress(0.4);
}
// ------------------------------------------------------------------------
/**
* STEP 3: Populate the green channel
*/
// Step 3.1: Populate the green channel at blue and red CFA positions
#ifdef _OPENMP
#pragma omp parallel for
#endif
for ( int row = 4; row < height - 4; row++ ) {
for ( int col = 4 + (FC( row, 0 ) & 1), indx = row * width + col; col < width - 4; col += 2, indx += 2 ) {
// 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 = ( fabs( 0.5f - VH_Central_Value ) < fabs( 0.5f - VH_Neighbourhood_Value ) ) ? VH_Neighbourhood_Value : VH_Central_Value;
// Cardinal gradients
float N_Grad = eps + fabs( cfa[indx - w1] - cfa[indx + w1] ) + fabs( cfa[indx] - cfa[indx - w2] ) + fabs( cfa[indx - w1] - cfa[indx - w3] ) + fabs( cfa[indx - w2] - cfa[indx - w4] );
float S_Grad = eps + fabs( cfa[indx + w1] - cfa[indx - w1] ) + fabs( cfa[indx] - cfa[indx + w2] ) + fabs( cfa[indx + w1] - cfa[indx + w3] ) + fabs( cfa[indx + w2] - cfa[indx + w4] );
float W_Grad = eps + fabs( cfa[indx - 1] - cfa[indx + 1] ) + fabs( cfa[indx] - cfa[indx - 2] ) + fabs( cfa[indx - 1] - cfa[indx - 3] ) + fabs( cfa[indx - 2] - cfa[indx - 4] );
float E_Grad = eps + fabs( cfa[indx + 1] - cfa[indx - 1] ) + fabs( cfa[indx] - cfa[indx + 2] ) + fabs( cfa[indx + 1] - cfa[indx + 3] ) + fabs( cfa[indx + 2] - cfa[indx + 4] );
// Cardinal pixel estimations
float N_Est = cfa[indx - w1] * ( 1.f + ( lpf[indx] - lpf[indx - w2] ) / ( eps + lpf[indx] + lpf[indx - w2] ) );
float S_Est = cfa[indx + w1] * ( 1.f + ( lpf[indx] - lpf[indx + w2] ) / ( eps + lpf[indx] + lpf[indx + w2] ) );
float W_Est = cfa[indx - 1] * ( 1.f + ( lpf[indx] - lpf[indx - 2] ) / ( eps + lpf[indx] + lpf[indx - 2] ) );
float E_Est = cfa[indx + 1] * ( 1.f + ( lpf[indx] - lpf[indx + 2] ) / ( eps + lpf[indx] + lpf[indx + 2] ) );
// Vertical and horizontal estimations
float V_Est = ( S_Grad * N_Est + N_Grad * S_Est ) / max(eps, N_Grad + S_Grad );
float H_Est = ( W_Grad * E_Est + E_Grad * W_Est ) / max(eps, E_Grad + W_Grad );
// G@B and G@R interpolation
rgb[indx][1] = LIM( VH_Disc * H_Est + ( 1.f - VH_Disc ) * V_Est, 0.f, 1.f );
}
}
free( lpf );
// RT ---------------------------------------------------------------------
if (plistener) {
plistener->setProgress(0.5);
}
// ------------------------------------------------------------------------
/**
* STEP 4: Populate the red and blue channels
*/
// Step 4.1: Calculate P/Q diagonal local discrimination
PQ_Dir = ( float ( * ) ) calloc( width * height, sizeof *PQ_Dir ); //merror ( PQ_Dir, "rcd_demosaicing_171125()" );
#ifdef _OPENMP
#pragma omp parallel for
#endif
for ( int row = 4; row < height - 4; row++ ) {
for ( int col = 4 + (FC( row, 0 ) & 1), indx = row * width + col; col < width - 4; col += 2, indx += 2 ) {
float P_Stat = max( - 18.f * cfa[indx] * cfa[indx - w1 - 1] - 18.f * cfa[indx] * cfa[indx + w1 + 1] - 36.f * cfa[indx] * cfa[indx - w2 - 2] - 36.f * cfa[indx] * cfa[indx + w2 + 2] + 18.f * cfa[indx] * cfa[indx - w3 - 3] + 18.f * cfa[indx] * cfa[indx + w3 + 3] - 2.f * cfa[indx] * cfa[indx - w4 - 4] - 2.f * cfa[indx] * cfa[indx + w4 + 4] + 38.f * cfa[indx] * cfa[indx] - 70.f * cfa[indx - w1 - 1] * cfa[indx + w1 + 1] - 12.f * cfa[indx - w1 - 1] * cfa[indx - w2 - 2] + 24.f * cfa[indx - w1 - 1] * cfa[indx + w2 + 2] - 38.f * cfa[indx - w1 - 1] * cfa[indx - w3 - 3] + 16.f * cfa[indx - w1 - 1] * cfa[indx + w3 + 3] + 12.f * cfa[indx - w1 - 1] * cfa[indx - w4 - 4] - 6.f * cfa[indx - w1 - 1] * cfa[indx + w4 + 4] + 46.f * cfa[indx - w1 - 1] * cfa[indx - w1 - 1] + 24.f * cfa[indx + w1 + 1] * cfa[indx - w2 - 2] - 12.f * cfa[indx + w1 + 1] * cfa[indx + w2 + 2] + 16.f * cfa[indx + w1 + 1] * cfa[indx - w3 - 3] - 38.f * cfa[indx + w1 + 1] * cfa[indx + w3 + 3] - 6.f * cfa[indx + w1 + 1] * cfa[indx - w4 - 4] + 12.f * cfa[indx + w1 + 1] * cfa[indx + w4 + 4] + 46.f * cfa[indx + w1 + 1] * cfa[indx + w1 + 1] + 14.f * cfa[indx - w2 - 2] * cfa[indx + w2 + 2] - 12.f * cfa[indx - w2 - 2] * cfa[indx + w3 + 3] - 2.f * cfa[indx - w2 - 2] * cfa[indx - w4 - 4] + 2.f * cfa[indx - w2 - 2] * cfa[indx + w4 + 4] + 11.f * cfa[indx - w2 - 2] * cfa[indx - w2 - 2] - 12.f * cfa[indx + w2 + 2] * cfa[indx - w3 - 3] + 2 * cfa[indx + w2 + 2] * cfa[indx - w4 - 4] - 2.f * cfa[indx + w2 + 2] * cfa[indx + w4 + 4] + 11.f * cfa[indx + w2 + 2] * cfa[indx + w2 + 2] + 2.f * cfa[indx - w3 - 3] * cfa[indx + w3 + 3] - 6.f * cfa[indx - w3 - 3] * cfa[indx - w4 - 4] + 10.f * cfa[indx - w3 - 3] * cfa[indx - w3 - 3] - 6.f * cfa[indx + w3 + 3] * cfa[indx + w4 + 4] + 10.f * cfa[indx + w3 + 3] * cfa[indx + w3 + 3] + 1.f * cfa[indx - w4 - 4] * cfa[indx - w4 - 4] + 1.f * cfa[indx + w4 + 4] * cfa[indx + w4 + 4], epssq );
float Q_Stat = max( - 18.f * cfa[indx] * cfa[indx + w1 - 1] - 18.f * cfa[indx] * cfa[indx - w1 + 1] - 36.f * cfa[indx] * cfa[indx + w2 - 2] - 36.f * cfa[indx] * cfa[indx - w2 + 2] + 18.f * cfa[indx] * cfa[indx + w3 - 3] + 18.f * cfa[indx] * cfa[indx - w3 + 3] - 2.f * cfa[indx] * cfa[indx + w4 - 4] - 2.f * cfa[indx] * cfa[indx - w4 + 4] + 38.f * cfa[indx] * cfa[indx] - 70.f * cfa[indx + w1 - 1] * cfa[indx - w1 + 1] - 12.f * cfa[indx + w1 - 1] * cfa[indx + w2 - 2] + 24.f * cfa[indx + w1 - 1] * cfa[indx - w2 + 2] - 38.f * cfa[indx + w1 - 1] * cfa[indx + w3 - 3] + 16.f * cfa[indx + w1 - 1] * cfa[indx - w3 + 3] + 12.f * cfa[indx + w1 - 1] * cfa[indx + w4 - 4] - 6.f * cfa[indx + w1 - 1] * cfa[indx - w4 + 4] + 46.f * cfa[indx + w1 - 1] * cfa[indx + w1 - 1] + 24.f * cfa[indx - w1 + 1] * cfa[indx + w2 - 2] - 12.f * cfa[indx - w1 + 1] * cfa[indx - w2 + 2] + 16.f * cfa[indx - w1 + 1] * cfa[indx + w3 - 3] - 38.f * cfa[indx - w1 + 1] * cfa[indx - w3 + 3] - 6.f * cfa[indx - w1 + 1] * cfa[indx + w4 - 4] + 12.f * cfa[indx - w1 + 1] * cfa[indx - w4 + 4] + 46.f * cfa[indx - w1 + 1] * cfa[indx - w1 + 1] + 14.f * cfa[indx + w2 - 2] * cfa[indx - w2 + 2] - 12.f * cfa[indx + w2 - 2] * cfa[indx - w3 + 3] - 2.f * cfa[indx + w2 - 2] * cfa[indx + w4 - 4] + 2.f * cfa[indx + w2 - 2] * cfa[indx - w4 + 4] + 11.f * cfa[indx + w2 - 2] * cfa[indx + w2 - 2] - 12.f * cfa[indx - w2 + 2] * cfa[indx + w3 - 3] + 2 * cfa[indx - w2 + 2] * cfa[indx + w4 - 4] - 2.f * cfa[indx - w2 + 2] * cfa[indx - w4 + 4] + 11.f * cfa[indx - w2 + 2] * cfa[indx - w2 + 2] + 2.f * cfa[indx + w3 - 3] * cfa[indx - w3 + 3] - 6.f * cfa[indx + w3 - 3] * cfa[indx + w4 - 4] + 10.f * cfa[indx + w3 - 3] * cfa[indx + w3 - 3] - 6.f * cfa[indx - w3 + 3] * cfa[indx - w4 + 4] + 10.f * cfa[indx - w3 + 3] * cfa[indx - w3 + 3] + 1.f * cfa[indx + w4 - 4] * cfa[indx + w4 - 4] + 1.f * cfa[indx - w4 + 4] * cfa[indx - w4 + 4], epssq );
PQ_Dir[indx] = P_Stat / ( P_Stat + Q_Stat );
}
}
// RT ---------------------------------------------------------------------
if (plistener) {
plistener->setProgress(0.7);
}
// -------------------------------------------------------------------------
// Step 4.2: Populate the red and blue channels at blue and red CFA positions
#ifdef _OPENMP
#pragma omp parallel for
#endif
for ( int row = 4; row < height - 4; row++ ) {
for ( int col = 4 + (FC( row, 0 ) & 1), indx = row * width + col, c = 2 - FC( row, col ); col < width - 4; col += 2, indx += 2 ) {
// Refined P/Q diagonal local discrimination
float PQ_Central_Value = PQ_Dir[indx];
float PQ_Neighbourhood_Value = 0.25f * ( PQ_Dir[indx - w1 - 1] + PQ_Dir[indx - w1 + 1] + PQ_Dir[indx + w1 - 1] + PQ_Dir[indx + w1 + 1] );
float PQ_Disc = ( fabs( 0.5f - PQ_Central_Value ) < fabs( 0.5f - PQ_Neighbourhood_Value ) ) ? PQ_Neighbourhood_Value : PQ_Central_Value;
// Diagonal gradients
float NW_Grad = eps + fabs( rgb[indx - w1 - 1][c] - rgb[indx + w1 + 1][c] ) + fabs( rgb[indx - w1 - 1][c] - rgb[indx - w3 - 3][c] ) + fabs( rgb[indx][1] - rgb[indx - w2 - 2][1] );
float NE_Grad = eps + fabs( rgb[indx - w1 + 1][c] - rgb[indx + w1 - 1][c] ) + fabs( rgb[indx - w1 + 1][c] - rgb[indx - w3 + 3][c] ) + fabs( rgb[indx][1] - rgb[indx - w2 + 2][1] );
float SW_Grad = eps + fabs( rgb[indx + w1 - 1][c] - rgb[indx - w1 + 1][c] ) + fabs( rgb[indx + w1 - 1][c] - rgb[indx + w3 - 3][c] ) + fabs( rgb[indx][1] - rgb[indx + w2 - 2][1] );
float SE_Grad = eps + fabs( rgb[indx + w1 + 1][c] - rgb[indx - w1 - 1][c] ) + fabs( rgb[indx + w1 + 1][c] - rgb[indx + w3 + 3][c] ) + fabs( rgb[indx][1] - rgb[indx + w2 + 2][1] );
// Diagonal colour differences
float NW_Est = rgb[indx - w1 - 1][c] - rgb[indx - w1 - 1][1];
float NE_Est = rgb[indx - w1 + 1][c] - rgb[indx - w1 + 1][1];
float SW_Est = rgb[indx + w1 - 1][c] - rgb[indx + w1 - 1][1];
float SE_Est = rgb[indx + w1 + 1][c] - rgb[indx + w1 + 1][1];
// P/Q estimations
float P_Est = ( NW_Grad * SE_Est + SE_Grad * NW_Est ) / max(eps, NW_Grad + SE_Grad );
float Q_Est = ( NE_Grad * SW_Est + SW_Grad * NE_Est ) / max(eps, NE_Grad + SW_Grad );
// R@B and B@R interpolation
rgb[indx][c] = LIM( rgb[indx][1] + ( 1.f - PQ_Disc ) * P_Est + PQ_Disc * Q_Est, 0.f, 1.f );
}
}
free( PQ_Dir );
// RT ---------------------------------------------------------------------
if (plistener) {
plistener->setProgress(0.825);
}
// -------------------------------------------------------------------------
// Step 4.3: Populate the red and blue channels at green CFA positions
#ifdef _OPENMP
#pragma omp parallel for
#endif
for ( int row = 4; row < height - 4; row++ ) {
for ( int col = 4 + (FC( row, 1 ) & 1), indx = row * width + col; col < width - 4; col += 2, indx += 2 ) {
// 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 = ( fabs( 0.5f - VH_Central_Value ) < fabs( 0.5f - VH_Neighbourhood_Value ) ) ? VH_Neighbourhood_Value : VH_Central_Value;
for ( int c = 0; c <= 2; c += 2 ) {
// Cardinal gradients
float N_Grad = eps + fabs( rgb[indx][1] - rgb[indx - w2][1] ) + fabs( rgb[indx - w1][c] - rgb[indx + w1][c] ) + fabs( rgb[indx - w1][c] - rgb[indx - w3][c] );
float S_Grad = eps + fabs( rgb[indx][1] - rgb[indx + w2][1] ) + fabs( rgb[indx + w1][c] - rgb[indx - w1][c] ) + fabs( rgb[indx + w1][c] - rgb[indx + w3][c] );
float W_Grad = eps + fabs( rgb[indx][1] - rgb[indx - 2][1] ) + fabs( rgb[indx - 1][c] - rgb[indx + 1][c] ) + fabs( rgb[indx - 1][c] - rgb[indx - 3][c] );
float E_Grad = eps + fabs( rgb[indx][1] - rgb[indx + 2][1] ) + fabs( rgb[indx + 1][c] - rgb[indx - 1][c] ) + fabs( rgb[indx + 1][c] - rgb[indx + 3][c] );
// Cardinal colour differences
float N_Est = rgb[indx - w1][c] - rgb[indx - w1][1];
float S_Est = rgb[indx + w1][c] - rgb[indx + w1][1];
float W_Est = rgb[indx - 1][c] - rgb[indx - 1][1];
float E_Est = rgb[indx + 1][c] - rgb[indx + 1][1];
// Vertical and horizontal estimations
float V_Est = ( N_Grad * S_Est + S_Grad * N_Est ) / max(eps, N_Grad + S_Grad );
float H_Est = ( E_Grad * W_Est + W_Grad * E_Est ) / max(eps, E_Grad + W_Grad );
// R@G and B@G interpolation
rgb[indx][c] = LIM( rgb[indx][1] + ( 1.f - VH_Disc ) * V_Est + VH_Disc * H_Est, 0.f, 1.f );
}
}
}
free(VH_Dir);
// RT ---------------------------------------------------------------------
if (plistener) {
plistener->setProgress(0.95);
}
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int row = 0; row < height; ++row) {
for (int col = 0, idx = row * width + col ; col < width; ++col, ++idx) {
red[row][col] = CLIP(rgb[idx][0] * 65535.f);
green[row][col] = CLIP(rgb[idx][1] * 65535.f);
blue[row][col] = CLIP(rgb[idx][2] * 65535.f);
}
}
border_interpolate2(width, height, 4);
if (plistener) {
plistener->setProgress(1);
}
// -------------------------------------------------------------------------
}
#define fcol(row,col) xtrans[(row)%6][(col)%6]
#define isgreen(row,col) (xtrans[(row)%3][(col)%3]&1)

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@ -2446,6 +2446,7 @@ const std::vector<const char*>& RAWParams::BayerSensor::getMethodStrings()
"vng4",
"dcb",
"ahd",
"rcd",
"fast",
"mono",
"none",

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@ -1180,6 +1180,7 @@ struct RAWParams {
VNG4,
DCB,
AHD,
RCD,
FAST,
MONO,
NONE,

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@ -2049,6 +2049,8 @@ void RawImageSource::demosaic(const RAWParams &raw)
fast_demosaic();
} else if (raw.bayersensor.method == RAWParams::BayerSensor::getMethodString(RAWParams::BayerSensor::Method::MONO) ) {
nodemosaic(true);
} else if (raw.bayersensor.method == RAWParams::BayerSensor::getMethodString(RAWParams::BayerSensor::Method::RCD) ) {
rcd_demosaic ();
} else {
nodemosaic(false);
}

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@ -248,6 +248,7 @@ protected:
void fast_demosaic();//Emil's code for fast demosaicing
void dcb_demosaic(int iterations, bool dcb_enhance);
void ahd_demosaic();
void rcd_demosaic();
void border_interpolate(unsigned int border, float (*image)[4], unsigned int start = 0, unsigned int end = 0);
void border_interpolate2(int winw, int winh, int lborders);
void dcb_initTileLimits(int &colMin, int &rowMin, int &colMax, int &rowMax, int x0, int y0, int border);