liz/rawTherapee
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Merge remote-tracking branch 'origin/dev' into filmnegative

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This commit is contained in:
rom9 2019-06-23 23:40:56 +02:00
commit 7040378dec
9 changed files with 759 additions and 705 deletions
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41
rtengine/CMakeLists.txt
View File

@ -30,15 +30,19 @@ link_directories("${PROJECT_SOURCE_DIR}/rtexif"
set(CAMCONSTSFILE "camconst.json")
set(RTENGINESOURCEFILES
badpixels.cc
CA_correct_RT.cc
EdgePreservingDecomposition.cc
FTblockDN.cc
PF_correct_RT.cc
ahd_demosaic_RT.cc
amaze_demosaic_RT.cc
CA_correct_RT.cc
cJSON.c
calc_distort.cc
camconst.cc
cfa_linedn_RT.cc
ciecam02.cc
cieimage.cc
cJSON.c
clutstore.cc
color.cc
colortemp.cc
@ -55,18 +59,13 @@ set(RTENGINESOURCEFILES
dual_demosaic_RT.cc
dynamicprofile.cc
eahd_demosaic.cc
EdgePreservingDecomposition.cc
fast_demo.cc
ffmanager.cc
filmnegativeproc.cc
flatcurves.cc
FTblockDN.cc
gamutwarning.cc
gauss.cc
green_equil_RT.cc
guidedfilter.cc
hilite_recon.cc
histmatching.cc
hphd_demosaic_RT.cc
iccjpeg.cc
iccstore.cc
@ -81,15 +80,10 @@ set(RTENGINESOURCEFILES
improcfun.cc
impulse_denoise.cc
init.cc
ipdehaze.cc
iplab2rgb.cc
iplabregions.cc
iplocalcontrast.cc
ipresize.cc
ipretinex.cc
ipshadowshighlights.cc
ipsharpen.cc
ipsoftlight.cc
iptransform.cc
ipvibrance.cc
ipwavelet.cc
@ -97,8 +91,8 @@ set(RTENGINESOURCEFILES
jpeg_ijg/jpeg_memsrc.cc
klt/convolve.cc
klt/error.cc
klt/klt_util.cc
klt/klt.cc
klt/klt_util.cc
klt/pnmio.cc
klt/pyramid.cc
klt/selectGoodFeatures.cc
@ -107,11 +101,8 @@ set(RTENGINESOURCEFILES
klt/writeFeatures.cc
labimage.cc
lcp.cc
lj92.c
loadinitial.cc
myfile.cc
pdaflinesfilter.cc
PF_correct_RT.cc
pipettebuffer.cc
pixelshift.cc
previewimage.cc
@ -123,17 +114,27 @@ set(RTENGINESOURCEFILES
rcd_demosaic.cc
refreshmap.cc
rt_algo.cc
rtlensfun.cc
rtthumbnail.cc
shmap.cc
simpleprocess.cc
slicer.cc
stdimagesource.cc
tmo_fattal02.cc
utils.cc
vng4_demosaic_RT.cc
rtlensfun.cc
tmo_fattal02.cc
iplocalcontrast.cc
histmatching.cc
pdaflinesfilter.cc
gamutwarning.cc
ipshadowshighlights.cc
xtrans_demosaic.cc
)
vng4_demosaic_RT.cc
ipsoftlight.cc
guidedfilter.cc
ipdehaze.cc
iplabregions.cc
lj92.c
)
if(LENSFUN_HAS_LOAD_DIRECTORY)
set_source_files_properties(rtlensfun.cc PROPERTIES COMPILE_DEFINITIONS RT_LENSFUN_HAS_LOAD_DIRECTORY)

576
rtengine/badpixels.cc Normal file
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@ -0,0 +1,576 @@
/*
* This file is part of RawTherapee.
*
* Copyright (c) 2004-2019 Gabor Horvath <hgabor@rawtherapee.com>
*
* 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 <http://www.gnu.org/licenses/>.
*/
#include "array2D.h"
#include "median.h"
#include "pixelsmap.h"
#include "rawimagesource.h"
namespace rtengine
{
/* interpolateBadPixelsBayer: correct raw pixels looking at the bitmap
* takes into consideration if there are multiple bad pixels in the neighborhood
*/
int RawImageSource::interpolateBadPixelsBayer(const PixelsMap &bitmapBads, array2D<float> &rawData)
{
constexpr float eps = 1.f;
int counter = 0;
#ifdef _OPENMP
#pragma omp parallel for reduction(+:counter) schedule(dynamic,16)
#endif
for (int row = 2; row < H - 2; ++row) {
for (int col = 2; col < W - 2; ++col) {
const int sk = bitmapBads.skipIfZero(col, row); //optimization for a stripe all zero
if (sk) {
col += sk - 1; //-1 is because of col++ in cycle
continue;
}
if (!bitmapBads.get(col, row)) {
continue;
}
float wtdsum = 0.f, norm = 0.f;
// diagonal interpolation
if (FC(row, col) == 1) {
// green channel. We can use closer pixels than for red or blue channel. Distance to center pixel is sqrt(2) => weighting is 0.70710678
// For green channel following pixels will be used for interpolation. Pixel to be interpolated is in center.
// 1 means that pixel is used in this step, if itself and his counterpart are not marked bad
// 0 0 0 0 0
// 0 1 0 1 0
// 0 0 0 0 0
// 0 1 0 1 0
// 0 0 0 0 0
for (int dx = -1; dx <= 1; dx += 2) {
if (bitmapBads.get(col + dx, row - 1) || bitmapBads.get(col - dx, row + 1)) {
continue;
}
const float dirwt = 0.70710678f / (fabsf(rawData[row - 1][col + dx] - rawData[row + 1][col - dx]) + eps);
wtdsum += dirwt * (rawData[row - 1][col + dx] + rawData[row + 1][col - dx]);
norm += dirwt;
}
} else {
// red and blue channel. Distance to center pixel is sqrt(8) => weighting is 0.35355339
// For red and blue channel following pixels will be used for interpolation. Pixel to be interpolated is in center.
// 1 means that pixel is used in this step, if itself and his counterpart are not marked bad
// 1 0 0 0 1
// 0 0 0 0 0
// 0 0 0 0 0
// 0 0 0 0 0
// 1 0 0 0 1
for (int dx = -2; dx <= 2; dx += 4) {
if (bitmapBads.get(col + dx, row - 2) || bitmapBads.get(col - dx, row + 2)) {
continue;
}
const float dirwt = 0.35355339f / (fabsf(rawData[row - 2][col + dx] - rawData[row + 2][col - dx]) + eps);
wtdsum += dirwt * (rawData[row - 2][col + dx] + rawData[row + 2][col - dx]);
norm += dirwt;
}
}
// channel independent. Distance to center pixel is 2 => weighting is 0.5
// Additionally for all channel following pixels will be used for interpolation. Pixel to be interpolated is in center.
// 1 means that pixel is used in this step, if itself and his counterpart are not marked bad
// 0 0 1 0 0
// 0 0 0 0 0
// 1 0 0 0 1
// 0 0 0 0 0
// 0 0 1 0 0
// horizontal interpolation
if (!(bitmapBads.get(col - 2, row) || bitmapBads.get(col + 2, row))) {
const float dirwt = 0.5f / (fabsf(rawData[row][col - 2] - rawData[row][col + 2]) + eps);
wtdsum += dirwt * (rawData[row][col - 2] + rawData[row][col + 2]);
norm += dirwt;
}
// vertical interpolation
if (!(bitmapBads.get(col, row - 2) || bitmapBads.get(col, row + 2))) {
const float dirwt = 0.5f / (fabsf(rawData[row - 2][col] - rawData[row + 2][col]) + eps);
wtdsum += dirwt * (rawData[row - 2][col] + rawData[row + 2][col]);
norm += dirwt;
}
if (LIKELY(norm > 0.f)) { // This means, we found at least one pair of valid pixels in the steps above, likelihood of this case is about 99.999%
rawData[row][col] = wtdsum / (2.f * norm); //gradient weighted average, Factor of 2.f is an optimization to avoid multiplications in former steps
counter++;
} else { //backup plan -- simple average. Same method for all channels. We could improve this, but it's really unlikely that this case happens
int tot = 0;
float sum = 0.f;
for (int dy = -2; dy <= 2; dy += 2) {
for (int dx = -2; dx <= 2; dx += 2) {
if (bitmapBads.get(col + dx, row + dy)) {
continue;
}
sum += rawData[row + dy][col + dx];
tot++;
}
}
if (tot > 0) {
rawData[row][col] = sum / tot;
counter ++;
}
}
}
}
return counter; // Number of interpolated pixels.
}
/* interpolateBadPixelsNcolors: correct raw pixels looking at the bitmap
* takes into consideration if there are multiple bad pixels in the neighborhood
*/
int RawImageSource::interpolateBadPixelsNColours(const PixelsMap &bitmapBads, const int colors)
{
constexpr float eps = 1.f;
int counter = 0;
#ifdef _OPENMP
#pragma omp parallel for reduction(+:counter) schedule(dynamic,16)
#endif
for (int row = 2; row < H - 2; ++row) {
for (int col = 2; col < W - 2; ++col) {
const int sk = bitmapBads.skipIfZero(col, row); //optimization for a stripe all zero
if (sk) {
col += sk - 1; //-1 is because of col++ in cycle
continue;
}
if (!bitmapBads.get(col, row)) {
continue;
}
float wtdsum[colors] = {};
float norm[colors] = {};
// diagonal interpolation
for (int dx = -1; dx <= 1; dx += 2) {
if (bitmapBads.get(col + dx, row - 1) || bitmapBads.get(col - dx, row + 1)) {
continue;
}
for (int c = 0; c < colors; ++c) {
const float dirwt = 0.70710678f / (fabsf(rawData[row - 1][(col + dx) * colors + c] - rawData[row + 1][(col - dx) * colors + c]) + eps);
wtdsum[c] += dirwt * (rawData[row - 1][(col + dx) * colors + c] + rawData[row + 1][(col - dx) * colors + c]);
norm[c] += dirwt;
}
}
// horizontal interpolation
if (!(bitmapBads.get(col - 1, row) || bitmapBads.get(col + 1, row))) {
for (int c = 0; c < colors; ++c) {
const float dirwt = 1.f / (fabsf(rawData[row][(col - 1) * colors + c] - rawData[row][(col + 1) * colors + c]) + eps);
wtdsum[c] += dirwt * (rawData[row][(col - 1) * colors + c] + rawData[row][(col + 1) * colors + c]);
norm[c] += dirwt;
}
}
// vertical interpolation
if (!(bitmapBads.get(col, row - 1) || bitmapBads.get(col, row + 1))) {
for (int c = 0; c < colors; ++c) {
const float dirwt = 1.f / (fabsf(rawData[row - 1][col * colors + c] - rawData[row + 1][col * colors + c]) + eps);
wtdsum[c] += dirwt * (rawData[row - 1][col * colors + c] + rawData[row + 1][col * colors + c]);
norm[c] += dirwt;
}
}
if (LIKELY(norm[0] > 0.f)) { // This means, we found at least one pair of valid pixels in the steps above, likelihood of this case is about 99.999%
for (int c = 0; c < colors; ++c) {
rawData[row][col * colors + c] = wtdsum[c] / (2.f * norm[c]); //gradient weighted average, Factor of 2.f is an optimization to avoid multiplications in former steps
}
counter++;
} else { //backup plan -- simple average. Same method for all channels. We could improve this, but it's really unlikely that this case happens
int tot = 0;
float sum[colors] = {};
for (int dy = -2; dy <= 2; dy += 2) {
for (int dx = -2; dx <= 2; dx += 2) {
if (bitmapBads.get(col + dx, row + dy)) {
continue;
}
for (int c = 0; c < colors; ++c) {
sum[c] += rawData[row + dy][(col + dx) * colors + c];
}
tot++;
}
}
if (tot > 0) {
for (int c = 0; c < colors; ++c) {
rawData[row][col * colors + c] = sum[c] / tot;
}
counter ++;
}
}
}
}
return counter; // Number of interpolated pixels.
}
/* interpolateBadPixelsXtrans: correct raw pixels looking at the bitmap
* takes into consideration if there are multiple bad pixels in the neighborhood
*/
int RawImageSource::interpolateBadPixelsXtrans(const PixelsMap &bitmapBads)
{
constexpr float eps = 1.f;
int counter = 0;
#ifdef _OPENMP
#pragma omp parallel for reduction(+:counter) schedule(dynamic,16)
#endif
for (int row = 2; row < H - 2; ++row) {
for (int col = 2; col < W - 2; ++col) {
const int skip = bitmapBads.skipIfZero(col, row); //optimization for a stripe all zero
if (skip) {
col += skip - 1; //-1 is because of col++ in cycle
continue;
}
if (!bitmapBads.get(col, row)) {
continue;
}
float wtdsum = 0.f, norm = 0.f;
const unsigned int pixelColor = ri->XTRANSFC(row, col);
if (pixelColor == 1) {
// green channel. A green pixel can either be a solitary green pixel or a member of a 2x2 square of green pixels
if (ri->XTRANSFC(row, col - 1) == ri->XTRANSFC(row, col + 1)) {
// If left and right neighbor have same color, then this is a solitary green pixel
// For these the following pixels will be used for interpolation. Pixel to be interpolated is in center and marked with a P.
// Pairs of pixels used in this step are numbered. A pair will be used if none of the pixels of the pair is marked bad
// 0 means, the pixel has a different color and will not be used
// 0 1 0 2 0
// 3 5 0 6 4
// 0 0 P 0 0
// 4 6 0 5 3
// 0 2 0 1 0
for (int dx = -1; dx <= 1; dx += 2) { // pixels marked 5 or 6 in above example. Distance to P is sqrt(2) => weighting is 0.70710678f
if (bitmapBads.get(col + dx, row - 1) || bitmapBads.get(col - dx, row + 1)) {
continue;
}
const float dirwt = 0.70710678f / (fabsf(rawData[row - 1][col + dx] - rawData[row + 1][col - dx]) + eps);
wtdsum += dirwt * (rawData[row - 1][col + dx] + rawData[row + 1][col - dx]);
norm += dirwt;
}
for (int dx = -1; dx <= 1; dx += 2) { // pixels marked 1 or 2 on above example. Distance to P is sqrt(5) => weighting is 0.44721359f
if (bitmapBads.get(col + dx, row - 2) || bitmapBads.get(col - dx, row + 2)) {
continue;
}
const float dirwt = 0.44721359f / (fabsf(rawData[row - 2][col + dx] - rawData[row + 2][col - dx]) + eps);
wtdsum += dirwt * (rawData[row - 2][col + dx] + rawData[row + 2][col - dx]);
norm += dirwt;
}
for (int dx = -2; dx <= 2; dx += 4) { // pixels marked 3 or 4 on above example. Distance to P is sqrt(5) => weighting is 0.44721359f
if (bitmapBads.get(col + dx, row - 1) || bitmapBads.get(col - dx, row + 1)) {
continue;
}
const float dirwt = 0.44721359f / (fabsf(rawData[row - 1][col + dx] - rawData[row + 1][col - dx]) + eps);
wtdsum += dirwt * (rawData[row - 1][col + dx] + rawData[row + 1][col - dx]);
norm += dirwt;
}
} else {
// this is a member of a 2x2 square of green pixels
// For these the following pixels will be used for interpolation. Pixel to be interpolated is at position P in the example.
// Pairs of pixels used in this step are numbered. A pair will be used if none of the pixels of the pair is marked bad
// 0 means, the pixel has a different color and will not be used
// 1 0 0 3
// 0 P 2 0
// 0 2 1 0
// 3 0 0 0
// pixels marked 1 in above example. Distance to P is sqrt(2) => weighting is 0.70710678f
const int offset1 = ri->XTRANSFC(row - 1, col - 1) == ri->XTRANSFC(row + 1, col + 1) ? 1 : -1;
if (!(bitmapBads.get(col - offset1, row - 1) || bitmapBads.get(col + offset1, row + 1))) {
const float dirwt = 0.70710678f / (fabsf(rawData[row - 1][col - offset1] - rawData[row + 1][col + offset1]) + eps);
wtdsum += dirwt * (rawData[row - 1][col - offset1] + rawData[row + 1][col + offset1]);
norm += dirwt;
}
// pixels marked 2 in above example. Distance to P is 1 => weighting is 1.f
int offsety = ri->XTRANSFC(row - 1, col) != 1 ? 1 : -1;
int offsetx = offset1 * offsety;
if (!(bitmapBads.get(col + offsetx, row) || bitmapBads.get(col, row + offsety))) {
const float dirwt = 1.f / (fabsf(rawData[row][col + offsetx] - rawData[row + offsety][col]) + eps);
wtdsum += dirwt * (rawData[row][col + offsetx] + rawData[row + offsety][col]);
norm += dirwt;
}
const int offsety2 = -offsety;
const int offsetx2 = -offsetx;
offsetx *= 2;
offsety *= 2;
// pixels marked 3 in above example. Distance to P is sqrt(5) => weighting is 0.44721359f
if (!(bitmapBads.get(col + offsetx, row + offsety2) || bitmapBads.get(col + offsetx2, row + offsety))) {
const float dirwt = 0.44721359f / (fabsf(rawData[row + offsety2][col + offsetx] - rawData[row + offsety][col + offsetx2]) + eps);
wtdsum += dirwt * (rawData[row + offsety2][col + offsetx] + rawData[row + offsety][col + offsetx2]);
norm += dirwt;
}
}
} else {
// red and blue channel.
// Each red or blue pixel has exactly one neighbor of same color in distance 2 and four neighbors of same color which can be reached by a move of a knight in chess.
// For the distance 2 pixel (marked with an X) we generate a virtual counterpart (marked with a V)
// For red and blue channel following pixels will be used for interpolation. Pixel to be interpolated is in center and marked with a P.
// Pairs of pixels used in this step are numbered except for distance 2 pixels which are marked X and V. A pair will be used if none of the pixels of the pair is marked bad
// 0 1 0 0 0 0 0 X 0 0 remaining cases are symmetric
// 0 0 0 0 2 1 0 0 0 2
// X 0 P 0 V 0 0 P 0 0
// 0 0 0 0 1 0 0 0 0 0
// 0 2 0 0 0 0 2 V 1 0
// Find two knight moves landing on a pixel of same color as the pixel to be interpolated.
// If we look at first and last row of 5x5 square, we will find exactly two knight pixels.
// Additionally we know that the column of this pixel has 1 or -1 horizontal distance to the center pixel
// When we find a knight pixel, we get its counterpart, which has distance (+-3,+-3), where the signs of distance depend on the corner of the found knight pixel.
// These pixels are marked 1 or 2 in above examples. Distance to P is sqrt(5) => weighting is 0.44721359f
// The following loop simply scans the four possible places. To keep things simple, it does not stop after finding two knight pixels, because it will not find more than two
for (int d1 = -2, offsety = 3; d1 <= 2; d1 += 4, offsety -= 6) {
for (int d2 = -1, offsetx = 3; d2 < 1; d2 += 2, offsetx -= 6) {
if (ri->XTRANSFC(row + d1, col + d2) == pixelColor) {
if (!(bitmapBads.get(col + d2, row + d1) || bitmapBads.get(col + d2 + offsetx, row + d1 + offsety))) {
const float dirwt = 0.44721359f / (fabsf(rawData[row + d1][col + d2] - rawData[row + d1 + offsety][col + d2 + offsetx]) + eps);
wtdsum += dirwt * (rawData[row + d1][col + d2] + rawData[row + d1 + offsety][col + d2 + offsetx]);
norm += dirwt;
}
}
}
}
// now scan for the pixel of same color in distance 2 in each direction (marked with an X in above examples).
bool distance2PixelFound = false;
int dx, dy;
// check horizontal
for (dx = -2, dy = 0; dx <= 2; dx += 4) {
if (ri->XTRANSFC(row, col + dx) == pixelColor) {
distance2PixelFound = true;
break;
}
}
if (!distance2PixelFound) {
// no distance 2 pixel on horizontal, check vertical
for (dx = 0, dy = -2; dy <= 2; dy += 4) {
if (ri->XTRANSFC(row + dy, col) == pixelColor) {
distance2PixelFound = true;
break;
}
}
}
// calculate the value of its virtual counterpart (marked with a V in above examples)
float virtualPixel;
if (dy == 0) {
virtualPixel = 0.5f * (rawData[row - 1][col - dx] + rawData[row + 1][col - dx]);
} else {
virtualPixel = 0.5f * (rawData[row - dy][col - 1] + rawData[row - dy][col + 1]);
}
// and weight as usual. Distance to P is 2 => weighting is 0.5f
const float dirwt = 0.5f / (fabsf(virtualPixel - rawData[row + dy][col + dx]) + eps);
wtdsum += dirwt * (virtualPixel + rawData[row + dy][col + dx]);
norm += dirwt;
}
if (LIKELY(norm > 0.f)) { // This means, we found at least one pair of valid pixels in the steps above, likelihood of this case is about 99.999%
rawData[row][col] = wtdsum / (2.f * norm); //gradient weighted average, Factor of 2.f is an optimization to avoid multiplications in former steps
counter++;
}
}
}
return counter; // Number of interpolated pixels.
}
/* Search for hot or dead pixels in the image and update the map
* For each pixel compare its value to the average of similar color surrounding
* (Taken from Emil Martinec idea)
* (Optimized by Ingo Weyrich 2013 and 2015)
*/
int RawImageSource::findHotDeadPixels(PixelsMap &bpMap, const float thresh, const bool findHotPixels, const bool findDeadPixels) const
{
const float varthresh = (20.0 * (thresh / 100.0) + 1.0) / 24.f;
// allocate temporary buffer
float* cfablur = new float[H * W];
// counter for dead or hot pixels
int counter = 0;
#ifdef _OPENMP
#pragma omp parallel
#endif
{
#ifdef _OPENMP
#pragma omp for schedule(dynamic,16) nowait
#endif
for (int i = 2; i < H - 2; i++) {
for (int j = 2; j < W - 2; j++) {
const float temp = median(rawData[i - 2][j - 2], rawData[i - 2][j], rawData[i - 2][j + 2],
rawData[i][j - 2], rawData[i][j], rawData[i][j + 2],
rawData[i + 2][j - 2], rawData[i + 2][j], rawData[i + 2][j + 2]);
cfablur[i * W + j] = rawData[i][j] - temp;
}
}
// process borders. Former version calculated the median using mirrored border which does not make sense because the original pixel loses weight
// Setting the difference between pixel and median for border pixels to zero should do the job not worse then former version
#ifdef _OPENMP
#pragma omp single
#endif
{
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < W; ++j) {
cfablur[i * W + j] = 0.f;
}
}
for (int i = 2; i < H - 2; ++i) {
for (int j = 0; j < 2; ++j) {
cfablur[i * W + j] = 0.f;
}
for (int j = W - 2; j < W; ++j) {
cfablur[i * W + j] = 0.f;
}
}
for (int i = H - 2; i < H; ++i) {
for (int j = 0; j < W; ++j) {
cfablur[i * W + j] = 0.f;
}
}
}
#ifdef _OPENMP
#pragma omp barrier // barrier because of nowait clause above
#pragma omp for reduction(+:counter) schedule(dynamic,16)
#endif
//cfa pixel heat/death evaluation
for (int rr = 2; rr < H - 2; ++rr) {
for (int cc = 2, rrmWpcc = rr * W + 2; cc < W - 2; ++cc, ++rrmWpcc) {
//evaluate pixel for heat/death
float pixdev = cfablur[rrmWpcc];
if (pixdev == 0.f) {
continue;
}
if ((!findDeadPixels) && pixdev < 0) {
continue;
}
if ((!findHotPixels) && pixdev > 0) {
continue;
}
pixdev = fabsf(pixdev);
float hfnbrave = -pixdev;
#ifdef __SSE2__
// sum up 5*4 = 20 values using SSE
// 10 fabs function calls and 10 float additions with SSE
vfloat sum = vabsf(LVFU(cfablur[(rr - 2) * W + cc - 2])) + vabsf(LVFU(cfablur[(rr - 1) * W + cc - 2]));
sum += vabsf(LVFU(cfablur[(rr) * W + cc - 2]));
sum += vabsf(LVFU(cfablur[(rr + 1) * W + cc - 2]));
sum += vabsf(LVFU(cfablur[(rr + 2) * W + cc - 2]));
// horizontally add the values and add the result to hfnbrave
hfnbrave += vhadd(sum);
// add remaining 5 values of last column
for (int mm = rr - 2; mm <= rr + 2; ++mm) {
hfnbrave += fabsf(cfablur[mm * W + cc + 2]);
}
#else
// 25 fabs function calls and 25 float additions without SSE
for (int mm = rr - 2; mm <= rr + 2; ++mm) {
for (int nn = cc - 2; nn <= cc + 2; ++nn) {
hfnbrave += fabsf(cfablur[mm * W + nn]);
}
}
#endif
if (pixdev > varthresh * hfnbrave) {
// mark the pixel as "bad"
bpMap.set(cc, rr);
counter++;
}
}//end of pixel evaluation
}
}//end of parallel processing
delete [] cfablur;
return counter;
}
int RawImageSource::findZeroPixels(PixelsMap &bpMap) const
{
int counter = 0;
#ifdef _OPENMP
#pragma omp parallel for reduction(+:counter) schedule(dynamic,16)
#endif
for (int i = 0; i < H; ++i) {
for (int j = 0; j < W; ++j) {
if (ri->data[i][j] == 0.f) {
bpMap.set(j, i);
counter++;
}
}
}
return counter;
}
}

1
rtengine/dfmanager.h
View File

@ -20,6 +20,7 @@
#include <glibmm/ustring.h>
#include <map>
#include <cmath>
#include "pixelsmap.h"
#include "rawimage.h"
namespace rtengine

1
rtengine/ffmanager.h
View File

@ -86,7 +86,6 @@ public:
protected:
typedef std::multimap<std::string, ffInfo> ffList_t;
typedef std::map<std::string, std::list<badPix> > bpList_t;
ffList_t ffList;
bool initialized;
Glib::ustring currentPath;

98
rtengine/pixelsmap.h Normal file
View File

@ -0,0 +1,98 @@
#pragma once
/*
* This file is part of RawTherapee.
*
* Copyright (c) 2004-2019 Gabor Horvath <hgabor@rawtherapee.com>
*
* 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 <http://www.gnu.org/licenses/>.
*/
#include <cstdint>
#include <vector>
#include "noncopyable.h"
namespace rtengine
{
struct badPix {
uint16_t x;
uint16_t y;
badPix(uint16_t xc, uint16_t yc): x(xc), y(yc) {}
};
class PixelsMap :
public NonCopyable
{
int w; // line width in base_t units
int h; // height
typedef unsigned long base_t;
static constexpr size_t base_t_size = sizeof(base_t);
base_t *pm;
public:
PixelsMap(int width, int height)
: w((width / (base_t_size * 8)) + 1), h(height), pm(new base_t[h * w])
{
clear();
}
~PixelsMap()
{
delete [] pm;
}
int width() const
{
return w;
}
int height() const
{
return h;
}
// if a pixel is set returns true
bool get(int x, int y) const
{
return (pm[y * w + x / (base_t_size * 8)] & (base_t)1 << (x % (base_t_size * 8))) != 0;
}
// set a pixel
void set(int x, int y)
{
pm[y * w + x / (base_t_size * 8)] |= (base_t)1 << (x % (base_t_size * 8)) ;
}
// set pixels from a list
int set(const std::vector<badPix> &bp)
{
for (std::vector<badPix>::const_iterator iter = bp.begin(); iter != bp.end(); ++iter) {
set(iter->x, iter->y);
}
return bp.size();
}
void clear()
{
memset(pm, 0, h * w * base_t_size);
}
// return 0 if at least one pixel in the word(base_t) is set, otherwise return the number of pixels to skip to the next word base_t
int skipIfZero(int x, int y) const
{
return pm[y * w + x / (base_t_size * 8)] == 0 ? base_t_size * 8 - x % (base_t_size * 8) : 0;
}
};
}

82
rtengine/procparams.cc
View File

@ -2763,23 +2763,23 @@ ProcParams::ProcParams()
void ProcParams::setDefaults()
{
toneCurve = ToneCurveParams();
toneCurve = {};
labCurve = LCurveParams();
labCurve = {};
rgbCurves = RGBCurvesParams();
rgbCurves = {};
localContrast = LocalContrastParams();
localContrast = {};
colorToning = ColorToningParams();
colorToning = {};
sharpenEdge = SharpenEdgeParams();
sharpenEdge = {};
sharpenMicro = SharpenMicroParams();
sharpenMicro = {};
sharpening = SharpeningParams();
sharpening = {};
prsharpening = SharpeningParams();
prsharpening = {};
prsharpening.contrast = 15.0;
prsharpening.method = "rld";
prsharpening.deconvamount = 100;
@ -2787,69 +2787,69 @@ void ProcParams::setDefaults()
prsharpening.deconviter = 100;
prsharpening.deconvdamping = 0;
vibrance = VibranceParams();
vibrance = {};
wb = WBParams();
wb = {};
colorappearance = ColorAppearanceParams();
colorappearance = {};
defringe = DefringeParams();
defringe = {};
impulseDenoise = ImpulseDenoiseParams();
impulseDenoise = {};
dirpyrDenoise = DirPyrDenoiseParams();
dirpyrDenoise = {};
epd = EPDParams();
epd = {};
fattal = FattalToneMappingParams();
fattal = {};
sh = SHParams();
sh = {};
crop = CropParams();
crop = {};
coarse = CoarseTransformParams();
coarse = {};
commonTrans = CommonTransformParams();
commonTrans = {};
rotate = RotateParams();
rotate = {};
distortion = DistortionParams();
distortion = {};
lensProf = LensProfParams();
lensProf = {};
perspective = PerspectiveParams();
perspective = {};
gradient = GradientParams();
gradient = {};
pcvignette = PCVignetteParams();
pcvignette = {};
vignetting = VignettingParams();
vignetting = {};
chmixer = ChannelMixerParams();
chmixer = {};
blackwhite = BlackWhiteParams();
blackwhite = {};
cacorrection = CACorrParams();
cacorrection = {};
resize = ResizeParams();
resize = {};
icm = ColorManagementParams();
icm = {};
wavelet = WaveletParams();
wavelet = {};
dirpyrequalizer = DirPyrEqualizerParams();
dirpyrequalizer = {};
hsvequalizer = HSVEqualizerParams();
hsvequalizer = {};
filmSimulation = FilmSimulationParams();
filmSimulation = {};
softlight = SoftLightParams();
softlight = {};
dehaze = DehazeParams();
dehaze = {};
raw = RAWParams();
raw = {};
metadata = MetaDataParams();
metadata = {};
exif.clear();
iptc.clear();

72
rtengine/rawimage.h
View File

@ -25,82 +25,10 @@
#include "dcraw.h"
#include "imageformat.h"
#include "noncopyable.h"
namespace rtengine
{
struct badPix {
uint16_t x;
uint16_t y;
badPix( uint16_t xc, uint16_t yc ): x(xc), y(yc) {}
};
class PixelsMap :
public NonCopyable
{
int w; // line width in base_t units
int h; // height
typedef unsigned long base_t;
static const size_t base_t_size = sizeof(base_t);
base_t *pm;
public:
PixelsMap(int width, int height )
: h(height)
{
w = (width / (base_t_size * 8)) + 1;
pm = new base_t [h * w ];
memset(pm, 0, h * w * base_t_size );
}
~PixelsMap()
{
delete [] pm;
}
int width() const
{
return w;
}
int height() const
{
return h;
}
// if a pixel is set returns true
bool get(int x, int y)
{
return (pm[y * w + x / (base_t_size * 8) ] & (base_t)1 << (x % (base_t_size * 8)) ) != 0;
}
// set a pixel
void set(int x, int y)
{
pm[y * w + x / (base_t_size * 8) ] |= (base_t)1 << (x % (base_t_size * 8)) ;
}
// set pixels from a list
int set( std::vector<badPix> &bp)
{
for(std::vector<badPix>::iterator iter = bp.begin(); iter != bp.end(); ++iter) {
set( iter->x, iter->y);
}
return bp.size();
}
void clear()
{
memset(pm, 0, h * w * base_t_size );
}
// return 0 if at least one pixel in the word(base_t) is set, otherwise return the number of pixels to skip to the next word base_t
int skipIfZero(int x, int y)
{
return pm[y * w + x / (base_t_size * 8) ] == 0 ? base_t_size * 8 - x % (base_t_size * 8) : 0;
}
};
class RawImage: public DCraw
{
public:

580
rtengine/rawimagesource.cc
View File

@ -930,542 +930,6 @@ void RawImageSource::convertColorSpace(Imagefloat* image, const ColorManagementP
colorSpaceConversion (image, cmp, wb, pre_mul, embProfile, camProfile, imatrices.xyz_cam, (static_cast<const FramesData*>(getMetaData()))->getCamera());
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
/* interpolateBadPixelsBayer: correct raw pixels looking at the bitmap
* takes into consideration if there are multiple bad pixels in the neighbourhood
*/
int RawImageSource::interpolateBadPixelsBayer( PixelsMap &bitmapBads, array2D<float> &rawData )
{
static const float eps = 1.f;
int counter = 0;
#ifdef _OPENMP
#pragma omp parallel for reduction(+:counter) schedule(dynamic,16)
#endif
for( int row = 2; row < H - 2; row++ ) {
for(int col = 2; col < W - 2; col++ ) {
int sk = bitmapBads.skipIfZero(col, row); //optimization for a stripe all zero
if( sk ) {
col += sk - 1; //-1 is because of col++ in cycle
continue;
}
if(!bitmapBads.get(col, row)) {
continue;
}
float wtdsum = 0.f, norm = 0.f;
// diagonal interpolation
if(FC(row, col) == 1) {
// green channel. We can use closer pixels than for red or blue channel. Distance to centre pixel is sqrt(2) => weighting is 0.70710678
// For green channel following pixels will be used for interpolation. Pixel to be interpolated is in centre.
// 1 means that pixel is used in this step, if itself and his counterpart are not marked bad
// 0 0 0 0 0
// 0 1 0 1 0
// 0 0 0 0 0
// 0 1 0 1 0
// 0 0 0 0 0
for( int dx = -1; dx <= 1; dx += 2) {
if( bitmapBads.get(col + dx, row - 1) || bitmapBads.get(col - dx, row + 1)) {
continue;
}
float dirwt = 0.70710678f / ( fabsf( rawData[row - 1][col + dx] - rawData[row + 1][col - dx]) + eps);
wtdsum += dirwt * (rawData[row - 1][col + dx] + rawData[row + 1][col - dx]);
norm += dirwt;
}
} else {
// red and blue channel. Distance to centre pixel is sqrt(8) => weighting is 0.35355339
// For red and blue channel following pixels will be used for interpolation. Pixel to be interpolated is in centre.
// 1 means that pixel is used in this step, if itself and his counterpart are not marked bad
// 1 0 0 0 1
// 0 0 0 0 0
// 0 0 0 0 0
// 0 0 0 0 0
// 1 0 0 0 1
for( int dx = -2; dx <= 2; dx += 4) {
if( bitmapBads.get(col + dx, row - 2) || bitmapBads.get(col - dx, row + 2)) {
continue;
}
float dirwt = 0.35355339f / ( fabsf( rawData[row - 2][col + dx] - rawData[row + 2][col - dx]) + eps);
wtdsum += dirwt * (rawData[row - 2][col + dx] + rawData[row + 2][col - dx]);
norm += dirwt;
}
}
// channel independent. Distance to centre pixel is 2 => weighting is 0.5
// Additionally for all channel following pixels will be used for interpolation. Pixel to be interpolated is in centre.
// 1 means that pixel is used in this step, if itself and his counterpart are not marked bad
// 0 0 1 0 0
// 0 0 0 0 0
// 1 0 0 0 1
// 0 0 0 0 0
// 0 0 1 0 0
// horizontal interpolation
if(!(bitmapBads.get(col - 2, row) || bitmapBads.get(col + 2, row))) {
float dirwt = 0.5f / ( fabsf( rawData[row][col - 2] - rawData[row][col + 2]) + eps);
wtdsum += dirwt * (rawData[row][col - 2] + rawData[row][col + 2]);
norm += dirwt;
}
// vertical interpolation
if(!(bitmapBads.get(col, row - 2) || bitmapBads.get(col, row + 2))) {
float dirwt = 0.5f / ( fabsf( rawData[row - 2][col] - rawData[row + 2][col]) + eps);
wtdsum += dirwt * (rawData[row - 2][col] + rawData[row + 2][col]);
norm += dirwt;
}
if (LIKELY(norm > 0.f)) { // This means, we found at least one pair of valid pixels in the steps above, likelihood of this case is about 99.999%
rawData[row][col] = wtdsum / (2.f * norm); //gradient weighted average, Factor of 2.f is an optimization to avoid multiplications in former steps
counter++;
} else { //backup plan -- simple average. Same method for all channels. We could improve this, but it's really unlikely that this case happens
int tot = 0;
float sum = 0;
for( int dy = -2; dy <= 2; dy += 2) {
for( int dx = -2; dx <= 2; dx += 2) {
if(bitmapBads.get(col + dx, row + dy)) {
continue;
}
sum += rawData[row + dy][col + dx];
tot++;
}
}
if (tot > 0) {
rawData[row][col] = sum / tot;
counter ++;
}
}
}
}
return counter; // Number of interpolated pixels.
}
/* interpolateBadPixels3Colours: correct raw pixels looking at the bitmap
* takes into consideration if there are multiple bad pixels in the neighbourhood
*/
int RawImageSource::interpolateBadPixelsNColours( PixelsMap &bitmapBads, const int colours )
{
static const float eps = 1.f;
int counter = 0;
#ifdef _OPENMP
#pragma omp parallel for reduction(+:counter) schedule(dynamic,16)
#endif
for( int row = 2; row < H - 2; row++ ) {
for(int col = 2; col < W - 2; col++ ) {
int sk = bitmapBads.skipIfZero(col, row); //optimization for a stripe all zero
if( sk ) {
col += sk - 1; //-1 is because of col++ in cycle
continue;
}
if(!bitmapBads.get(col, row)) {
continue;
}
float wtdsum[colours], norm[colours];
for (int i = 0; i < colours; ++i) {
wtdsum[i] = norm[i] = 0.f;
}
// diagonal interpolation
for( int dx = -1; dx <= 1; dx += 2) {
if( bitmapBads.get(col + dx, row - 1) || bitmapBads.get(col - dx, row + 1)) {
continue;
}
for(int c = 0; c < colours; c++) {
float dirwt = 0.70710678f / ( fabsf( rawData[row - 1][(col + dx) * colours + c] - rawData[row + 1][(col - dx) * colours + c]) + eps);
wtdsum[c] += dirwt * (rawData[row - 1][(col + dx) * colours + c] + rawData[row + 1][(col - dx) * colours + c]);
norm[c] += dirwt;
}
}
// horizontal interpolation
if(!(bitmapBads.get(col - 1, row) || bitmapBads.get(col + 1, row))) {
for(int c = 0; c < colours; c++) {
float dirwt = 1.f / ( fabsf( rawData[row][(col - 1) * colours + c] - rawData[row][(col + 1) * colours + c]) + eps);
wtdsum[c] += dirwt * (rawData[row][(col - 1) * colours + c] + rawData[row][(col + 1) * colours + c]);
norm[c] += dirwt;
}
}
// vertical interpolation
if(!(bitmapBads.get(col, row - 1) || bitmapBads.get(col, row + 1))) {
for(int c = 0; c < colours; c++) {
float dirwt = 1.f / ( fabsf( rawData[row - 1][col * colours + c] - rawData[row + 1][col * colours + c]) + eps);
wtdsum[c] += dirwt * (rawData[row - 1][col * colours + c] + rawData[row + 1][col * colours + c]);
norm[c] += dirwt;
}
}
if (LIKELY(norm[0] > 0.f)) { // This means, we found at least one pair of valid pixels in the steps above, likelihood of this case is about 99.999%
for(int c = 0; c < colours; c++) {
rawData[row][col * colours + c] = wtdsum[c] / (2.f * norm[c]); //gradient weighted average, Factor of 2.f is an optimization to avoid multiplications in former steps
}
counter++;
} else { //backup plan -- simple average. Same method for all channels. We could improve this, but it's really unlikely that this case happens
int tot = 0;
float sum[colours];
for (int i = 0; i < colours; ++i) {
sum[i] = 0.f;
}
for( int dy = -2; dy <= 2; dy += 2) {
for( int dx = -2; dx <= 2; dx += 2) {
if(bitmapBads.get(col + dx, row + dy)) {
continue;
}
for(int c = 0; c < colours; c++) {
sum[c] += rawData[row + dy][(col + dx) * colours + c];
}
tot++;
}
}
if (tot > 0) {
for(int c = 0; c < colours; c++) {
rawData[row][col * colours + c] = sum[c] / tot;
}
counter ++;
}
}
}
}
return counter; // Number of interpolated pixels.
}
/* interpolateBadPixelsXtrans: correct raw pixels looking at the bitmap
* takes into consideration if there are multiple bad pixels in the neighbourhood
*/
int RawImageSource::interpolateBadPixelsXtrans( PixelsMap &bitmapBads )
{
static const float eps = 1.f;
int counter = 0;
#ifdef _OPENMP
#pragma omp parallel for reduction(+:counter) schedule(dynamic,16)
#endif
for( int row = 2; row < H - 2; row++ ) {
for(int col = 2; col < W - 2; col++ ) {
int skip = bitmapBads.skipIfZero(col, row); //optimization for a stripe all zero
if( skip ) {
col += skip - 1; //-1 is because of col++ in cycle
continue;
}
if(!bitmapBads.get(col, row)) {
continue;
}
float wtdsum = 0.f, norm = 0.f;
unsigned int pixelColor = ri->XTRANSFC(row, col);
if(pixelColor == 1) {
// green channel. A green pixel can either be a solitary green pixel or a member of a 2x2 square of green pixels
if(ri->XTRANSFC(row, col - 1) == ri->XTRANSFC(row, col + 1)) {
// If left and right neighbour have same colour, then this is a solitary green pixel
// For these the following pixels will be used for interpolation. Pixel to be interpolated is in centre and marked with a P.
// Pairs of pixels used in this step are numbered. A pair will be used if none of the pixels of the pair is marked bad
// 0 means, the pixel has a different colour and will not be used
// 0 1 0 2 0
// 3 5 0 6 4
// 0 0 P 0 0
// 4 6 0 5 3
// 0 2 0 1 0
for( int dx = -1; dx <= 1; dx += 2) { // pixels marked 5 or 6 in above example. Distance to P is sqrt(2) => weighting is 0.70710678f
if( bitmapBads.get(col + dx, row - 1) || bitmapBads.get(col - dx, row + 1)) {
continue;
}
float dirwt = 0.70710678f / ( fabsf( rawData[row - 1][col + dx] - rawData[row + 1][col - dx]) + eps);
wtdsum += dirwt * (rawData[row - 1][col + dx] + rawData[row + 1][col - dx]);
norm += dirwt;
}
for( int dx = -1; dx <= 1; dx += 2) { // pixels marked 1 or 2 on above example. Distance to P is sqrt(5) => weighting is 0.44721359f
if( bitmapBads.get(col + dx, row - 2) || bitmapBads.get(col - dx, row + 2)) {
continue;
}
float dirwt = 0.44721359f / ( fabsf( rawData[row - 2][col + dx] - rawData[row + 2][col - dx]) + eps);
wtdsum += dirwt * (rawData[row - 2][col + dx] + rawData[row + 2][col - dx]);
norm += dirwt;
}
for( int dx = -2; dx <= 2; dx += 4) { // pixels marked 3 or 4 on above example. Distance to P is sqrt(5) => weighting is 0.44721359f
if( bitmapBads.get(col + dx, row - 1) || bitmapBads.get(col - dx, row + 1)) {
continue;
}
float dirwt = 0.44721359f / ( fabsf( rawData[row - 1][col + dx] - rawData[row + 1][col - dx]) + eps);
wtdsum += dirwt * (rawData[row - 1][col + dx] + rawData[row + 1][col - dx]);
norm += dirwt;
}
} else {
// this is a member of a 2x2 square of green pixels
// For these the following pixels will be used for interpolation. Pixel to be interpolated is at position P in the example.
// Pairs of pixels used in this step are numbered. A pair will be used if none of the pixels of the pair is marked bad
// 0 means, the pixel has a different colour and will not be used
// 1 0 0 3
// 0 P 2 0
// 0 2 1 0
// 3 0 0 0
// pixels marked 1 in above example. Distance to P is sqrt(2) => weighting is 0.70710678f
int offset1 = ri->XTRANSFC(row - 1, col - 1) == ri->XTRANSFC(row + 1, col + 1) ? 1 : -1;
if( !(bitmapBads.get(col - offset1, row - 1) || bitmapBads.get(col + offset1, row + 1))) {
float dirwt = 0.70710678f / ( fabsf( rawData[row - 1][col - offset1] - rawData[row + 1][col + offset1]) + eps);
wtdsum += dirwt * (rawData[row - 1][col - offset1] + rawData[row + 1][col + offset1]);
norm += dirwt;
}
// pixels marked 2 in above example. Distance to P is 1 => weighting is 1.f
int offsety = (ri->XTRANSFC(row - 1, col) != 1 ? 1 : -1);
int offsetx = offset1 * offsety;
if( !(bitmapBads.get(col + offsetx, row) || bitmapBads.get(col, row + offsety))) {
float dirwt = 1.f / ( fabsf( rawData[row][col + offsetx] - rawData[row + offsety][col]) + eps);
wtdsum += dirwt * (rawData[row][col + offsetx] + rawData[row + offsety][col]);
norm += dirwt;
}
int offsety2 = -offsety;
int offsetx2 = -offsetx;
offsetx *= 2;
offsety *= 2;
// pixels marked 3 in above example. Distance to P is sqrt(5) => weighting is 0.44721359f
if( !(bitmapBads.get(col + offsetx, row + offsety2) || bitmapBads.get(col + offsetx2, row + offsety))) {
float dirwt = 0.44721359f / ( fabsf( rawData[row + offsety2][col + offsetx] - rawData[row + offsety][col + offsetx2]) + eps);
wtdsum += dirwt * (rawData[row + offsety2][col + offsetx] + rawData[row + offsety][col + offsetx2]);
norm += dirwt;
}
}
} else {
// red and blue channel.
// Each red or blue pixel has exactly one neighbour of same colour in distance 2 and four neighbours of same colour which can be reached by a move of a knight in chess.
// For the distance 2 pixel (marked with an X) we generate a virtual counterpart (marked with a V)
// For red and blue channel following pixels will be used for interpolation. Pixel to be interpolated is in centre and marked with a P.
// Pairs of pixels used in this step are numbered except for distance 2 pixels which are marked X and V. A pair will be used if none of the pixels of the pair is marked bad
// 0 1 0 0 0 0 0 X 0 0 remaining cases are symmetric
// 0 0 0 0 2 1 0 0 0 2
// X 0 P 0 V 0 0 P 0 0
// 0 0 0 0 1 0 0 0 0 0
// 0 2 0 0 0 0 2 V 1 0
// Find two knight moves landing on a pixel of same colour as the pixel to be interpolated.
// If we look at first and last row of 5x5 square, we will find exactly two knight pixels.
// Additionally we know that the column of this pixel has 1 or -1 horizontal distance to the centre pixel
// When we find a knight pixel, we get its counterpart, which has distance (+-3,+-3), where the signs of distance depend on the corner of the found knight pixel.
// These pixels are marked 1 or 2 in above examples. Distance to P is sqrt(5) => weighting is 0.44721359f
// The following loop simply scans the four possible places. To keep things simple, it does not stop after finding two knight pixels, because it will not find more than two
for(int d1 = -2, offsety = 3; d1 <= 2; d1 += 4, offsety -= 6) {
for(int d2 = -1, offsetx = 3; d2 < 1; d2 += 2, offsetx -= 6) {
if(ri->XTRANSFC(row + d1, col + d2) == pixelColor) {
if( !(bitmapBads.get(col + d2, row + d1) || bitmapBads.get(col + d2 + offsetx, row + d1 + offsety))) {
float dirwt = 0.44721359f / ( fabsf( rawData[row + d1][col + d2] - rawData[row + d1 + offsety][col + d2 + offsetx]) + eps);
wtdsum += dirwt * (rawData[row + d1][col + d2] + rawData[row + d1 + offsety][col + d2 + offsetx]);
norm += dirwt;
}
}
}
}
// now scan for the pixel of same colour in distance 2 in each direction (marked with an X in above examples).
bool distance2PixelFound = false;
int dx, dy;
// check horizontal
for(dx = -2, dy = 0; dx <= 2 && !distance2PixelFound; dx += 4)
if(ri->XTRANSFC(row, col + dx) == pixelColor) {
distance2PixelFound = true;
break;
}
if(!distance2PixelFound)
// no distance 2 pixel on horizontal, check vertical
for(dx = 0, dy = -2; dy <= 2 && !distance2PixelFound; dy += 4)
if(ri->XTRANSFC(row + dy, col) == pixelColor) {
distance2PixelFound = true;
break;
}
// calculate the value of its virtual counterpart (marked with a V in above examples)
float virtualPixel;
if(dy == 0) {
virtualPixel = 0.5f * (rawData[row - 1][col - dx] + rawData[row + 1][col - dx]);
} else {
virtualPixel = 0.5f * (rawData[row - dy][col - 1] + rawData[row - dy][col + 1]);
}
// and weight as usual. Distance to P is 2 => weighting is 0.5f
float dirwt = 0.5f / ( fabsf( virtualPixel - rawData[row + dy][col + dx]) + eps);
wtdsum += dirwt * (virtualPixel + rawData[row + dy][col + dx]);
norm += dirwt;
}
if (LIKELY(norm > 0.f)) { // This means, we found at least one pair of valid pixels in the steps above, likelihood of this case is about 99.999%
rawData[row][col] = wtdsum / (2.f * norm); //gradient weighted average, Factor of 2.f is an optimization to avoid multiplications in former steps
counter++;
}
}
}
return counter; // Number of interpolated pixels.
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
/* Search for hot or dead pixels in the image and update the map
* For each pixel compare its value to the average of similar colour surrounding
* (Taken from Emil Martinec idea)
* (Optimized by Ingo Weyrich 2013 and 2015)
*/
int RawImageSource::findHotDeadPixels( PixelsMap &bpMap, float thresh, bool findHotPixels, bool findDeadPixels )
{
float varthresh = (20.0 * (thresh / 100.0) + 1.0 ) / 24.f;
// allocate temporary buffer
float* cfablur;
cfablur = (float (*)) malloc (H * W * sizeof * cfablur);
// counter for dead or hot pixels
int counter = 0;
#ifdef _OPENMP
#pragma omp parallel
#endif
{
#ifdef _OPENMP
#pragma omp for schedule(dynamic,16) nowait
#endif
for (int i = 2; i < H - 2; i++) {
for (int j = 2; j < W - 2; j++) {
const float& temp = median(rawData[i - 2][j - 2], rawData[i - 2][j], rawData[i - 2][j + 2],
rawData[i][j - 2], rawData[i][j], rawData[i][j + 2],
rawData[i + 2][j - 2], rawData[i + 2][j], rawData[i + 2][j + 2]);
cfablur[i * W + j] = rawData[i][j] - temp;
}
}
// process borders. Former version calculated the median using mirrored border which does not make sense because the original pixel loses weight
// Setting the difference between pixel and median for border pixels to zero should do the job not worse then former version
#ifdef _OPENMP
#pragma omp single
#endif
{
for(int i = 0; i < 2; i++) {
for(int j = 0; j < W; j++) {
cfablur[i * W + j] = 0.f;
}
}
for(int i = 2; i < H - 2; i++) {
for(int j = 0; j < 2; j++) {
cfablur[i * W + j] = 0.f;
}
for(int j = W - 2; j < W; j++) {
cfablur[i * W + j] = 0.f;
}
}
for(int i = H - 2; i < H; i++) {
for(int j = 0; j < W; j++) {
cfablur[i * W + j] = 0.f;
}
}
}
#ifdef _OPENMP
#pragma omp barrier // barrier because of nowait clause above
#pragma omp for reduction(+:counter) schedule(dynamic,16)
#endif
//cfa pixel heat/death evaluation
for (int rr = 2; rr < H - 2; rr++) {
int rrmWpcc = rr * W + 2;
for (int cc = 2; cc < W - 2; cc++, rrmWpcc++) {
//evaluate pixel for heat/death
float pixdev = cfablur[rrmWpcc];
if(pixdev == 0.f) {
continue;
}
if((!findDeadPixels) && pixdev < 0) {
continue;
}
if((!findHotPixels) && pixdev > 0) {
continue;
}
pixdev = fabsf(pixdev);
float hfnbrave = -pixdev;
#ifdef __SSE2__
// sum up 5*4 = 20 values using SSE
// 10 fabs function calls and float 10 additions with SSE
vfloat sum = vabsf(LVFU(cfablur[(rr - 2) * W + cc - 2])) + vabsf(LVFU(cfablur[(rr - 1) * W + cc - 2]));
sum += vabsf(LVFU(cfablur[(rr) * W + cc - 2]));
sum += vabsf(LVFU(cfablur[(rr + 1) * W + cc - 2]));
sum += vabsf(LVFU(cfablur[(rr + 2) * W + cc - 2]));
// horizontally add the values and add the result to hfnbrave
hfnbrave += vhadd(sum);
// add remaining 5 values of last column
for (int mm = rr - 2; mm <= rr + 2; mm++) {
hfnbrave += fabsf(cfablur[mm * W + cc + 2]);
}
#else
// 25 fabs function calls and 25 float additions without SSE
for (int mm = rr - 2; mm <= rr + 2; mm++) {
for (int nn = cc - 2; nn <= cc + 2; nn++) {
hfnbrave += fabsf(cfablur[mm * W + nn]);
}
}
#endif
if (pixdev > varthresh * hfnbrave) {
// mark the pixel as "bad"
bpMap.set(cc, rr);
counter++;
}
}//end of pixel evaluation
}
}//end of parallel processing
free (cfablur);
return counter;
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
void RawImageSource::getFullSize (int& w, int& h, int tr)
{
@ -1741,23 +1205,13 @@ void RawImageSource::preprocess (const RAWParams &raw, const LensProfParams &le
printf( "Subtracting Darkframe:%s\n", rid->get_filename().c_str());
}
PixelsMap *bitmapBads = nullptr;
std::unique_ptr<PixelsMap> bitmapBads;
int totBP = 0; // Hold count of bad pixels to correct
if(ri->zeroIsBad()) { // mark all pixels with value zero as bad, has to be called before FF and DF. dcraw sets this flag only for some cameras (mainly Panasonic and Leica)
bitmapBads = new PixelsMap(W, H);
#ifdef _OPENMP
#pragma omp parallel for reduction(+:totBP) schedule(dynamic,16)
#endif
for(int i = 0; i < H; i++)
for(int j = 0; j < W; j++) {
if(ri->data[i][j] == 0.f) {
bitmapBads->set(j, i);
totBP++;
}
}
bitmapBads.reset(new PixelsMap(W, H));
totBP = findZeroPixels(*(bitmapBads.get()));
if( settings->verbose) {
printf( "%d pixels with value zero marked as bad pixels\n", totBP);
@ -1821,10 +1275,10 @@ void RawImageSource::preprocess (const RAWParams &raw, const LensProfParams &le
if( bp ) {
if(!bitmapBads) {
bitmapBads = new PixelsMap(W, H);
bitmapBads.reset(new PixelsMap(W, H));
}
totBP += bitmapBads->set( *bp );
totBP += bitmapBads->set(*bp);
if( settings->verbose ) {
std::cout << "Correcting " << bp->size() << " pixels from .badpixels" << std::endl;
@ -1842,10 +1296,10 @@ void RawImageSource::preprocess (const RAWParams &raw, const LensProfParams &le
if(bp) {
if(!bitmapBads) {
bitmapBads = new PixelsMap(W, H);
bitmapBads.reset(new PixelsMap(W, H));
}
totBP += bitmapBads->set( *bp );
totBP += bitmapBads->set(*bp);
if( settings->verbose && !bp->empty()) {
std::cout << "Correcting " << bp->size() << " hotpixels from darkframe" << std::endl;
@ -1917,10 +1371,10 @@ void RawImageSource::preprocess (const RAWParams &raw, const LensProfParams &le
}
if(!bitmapBads) {
bitmapBads = new PixelsMap(W, H);
bitmapBads.reset(new PixelsMap(W, H));
}
int nFound = findHotDeadPixels( *bitmapBads, raw.hotdeadpix_thresh, raw.hotPixelFilter, raw.deadPixelFilter );
int nFound = findHotDeadPixels(*(bitmapBads.get()), raw.hotdeadpix_thresh, raw.hotPixelFilter, raw.deadPixelFilter );
totBP += nFound;
if( settings->verbose && nFound > 0) {
@ -1932,10 +1386,10 @@ void RawImageSource::preprocess (const RAWParams &raw, const LensProfParams &le
PDAFLinesFilter f(ri);
if (!bitmapBads) {
bitmapBads = new PixelsMap(W, H);
bitmapBads.reset(new PixelsMap(W, H));
}
int n = f.mark(rawData, *bitmapBads);
int n = f.mark(rawData, *(bitmapBads.get()));
totBP += n;
if (n > 0) {
@ -1999,15 +1453,15 @@ void RawImageSource::preprocess (const RAWParams &raw, const LensProfParams &le
if ( ri->getSensorType() == ST_BAYER ) {
if(numFrames == 4) {
for(int i = 0; i < 4; ++i) {
interpolateBadPixelsBayer( *bitmapBads, *rawDataFrames[i] );
interpolateBadPixelsBayer(*(bitmapBads.get()), *rawDataFrames[i]);
}
} else {
interpolateBadPixelsBayer( *bitmapBads, rawData );
interpolateBadPixelsBayer(*(bitmapBads.get()), rawData);
}
} else if ( ri->getSensorType() == ST_FUJI_XTRANS ) {
interpolateBadPixelsXtrans( *bitmapBads );
interpolateBadPixelsXtrans(*(bitmapBads.get()));
} else {
interpolateBadPixelsNColours( *bitmapBads, ri->get_colors() );
interpolateBadPixelsNColours(*(bitmapBads.get()), ri->get_colors());
}
}
@ -2060,10 +1514,6 @@ void RawImageSource::preprocess (const RAWParams &raw, const LensProfParams &le
printf("Preprocessing: %d usec\n", t2.etime(t1));
}
if(bitmapBads) {
delete bitmapBads;
}
rawDirty = true;
return;
}

13
rtengine/rawimagesource.h
View File

@ -28,6 +28,7 @@
#include "dcp.h"
#include "iimage.h"
#include "imagesource.h"
#include "pixelsmap.h"
#define HR_SCALE 2
@ -100,7 +101,7 @@ protected:
void transformRect (const PreviewProps &pp, int tran, int &sx1, int &sy1, int &width, int &height, int &fw);
void transformPosition (int x, int y, int tran, int& tx, int& ty);
unsigned FC(int row, int col)
unsigned FC(int row, int col) const
{
return ri->FC(row, col);
}
@ -258,11 +259,11 @@ protected:
);
void ddct8x8s(int isgn, float a[8][8]);
int interpolateBadPixelsBayer( PixelsMap &bitmapBads, array2D<float> &rawData );
int interpolateBadPixelsNColours( PixelsMap &bitmapBads, const int colours );
int interpolateBadPixelsXtrans( PixelsMap &bitmapBads );
int findHotDeadPixels( PixelsMap &bpMap, float thresh, bool findHotPixels, bool findDeadPixels );
int interpolateBadPixelsBayer(const PixelsMap &bitmapBads, array2D<float> &rawData);
int interpolateBadPixelsNColours(const PixelsMap &bitmapBads, int colours);
int interpolateBadPixelsXtrans(const PixelsMap &bitmapBads);
int findHotDeadPixels(PixelsMap &bpMap, float thresh, bool findHotPixels, bool findDeadPixels) const;
int findZeroPixels(PixelsMap &bpMap) const;
void cfa_linedn (float linenoiselevel, bool horizontal, bool vertical, const CFALineDenoiseRowBlender &rowblender);//Emil's line denoise
void green_equilibrate_global (array2D<float> &rawData);