rawTherapee/rtengine/histmatching.cc
2018-01-18 14:17:51 +01:00

212 lines
6.7 KiB
C++

/* -*- C++ -*-
*
* This file is part of RawTherapee.
*
* Copyright (c) 2018 Alberto Griggio <alberto.griggio@gmail.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 "rawimagesource.h"
#include "rtthumbnail.h"
#include "curves.h"
#include "color.h"
#include "rt_math.h"
#include "iccstore.h"
#include "../rtgui/mydiagonalcurve.h"
#include "improcfun.h"
#define BENCHMARK
#include "StopWatch.h"
#include <iostream>
namespace rtengine {
extern const Settings *settings;
namespace {
std::vector<int> getCdf(const IImage8 &img)
{
std::vector<int> ret(256);
for (int y = 0; y < img.getHeight(); ++y) {
for (int x = 0; x < img.getWidth(); ++x) {
int lum = LIM(0, int(Color::rgbLuminance(float(img.r(y, x)), float(img.g(y, x)), float(img.b(y, x)))), 255);
++ret[lum];
}
}
int sum = 0;
for (size_t i = 0; i < ret.size(); ++i) {
sum += ret[i];
ret[i] = sum;
}
return ret;
}
int findMatch(int val, const std::vector<int> &cdf, int j)
{
if (cdf[j] <= val) {
for (; j < int(cdf.size()); ++j) {
if (cdf[j] == val) {
return j;
} else if (cdf[j] > val) {
return (cdf[j] - val <= val - cdf[j-1] ? j : j-1);
}
}
return 255;
} else {
for (; j >= 0; --j) {
if (cdf[j] == val) {
return j;
} else if (cdf[j] < val) {
return (val - cdf[j] <= cdf[j+1] - val ? j : j+1);
}
}
return 0;
}
}
void mappingToCurve(const std::vector<int> &mapping, std::vector<double> &curve)
{
curve.clear();
const int npoints = 8;
int idx = 1;
for (; idx < int(mapping.size()); ++idx) {
if (mapping[idx] >= idx) {
break;
}
}
int step = max(int(mapping.size())/npoints, 1);
auto coord = [](int v) -> double { return double(v)/255.0; };
auto doit =
[&](int start, int stop, int step, bool addstart) -> void
{
int prev = start;
if (addstart) {
curve.push_back(coord(start));
curve.push_back(coord(mapping[start]));
}
for (int i = start; i < stop; ++i) {
int v = mapping[i];
bool change = i > 0 && v != mapping[i-1];
int diff = i - prev;
if (change && std::abs(diff - step) <= 1) {
curve.push_back(coord(i));
curve.push_back(coord(v));
prev = i;
}
}
};
doit(0, idx, idx > step ? step : idx / 2, true);
doit(idx, int(mapping.size()), step, idx - step > step / 2);
if (curve.size() <= 2 || curve.back() < 0.99 || (1 - curve[curve.size()-2] > step / 512.0 && curve.back() < coord(mapping.back()))) {
curve.emplace_back(1.0);
curve.emplace_back(coord(mapping.back()));
}
if (curve.size() < 4) {
curve = { DCT_Linear }; // not enough points, fall back to linear
} else {
curve.insert(curve.begin(), DCT_Spline);
}
}
} // namespace
void RawImageSource::getAutoMatchedToneCurve(std::vector<double> &outCurve)
{
BENCHFUN
if (settings->verbose) {
std::cout << "performing histogram matching for " << getFileName() << " on the embedded thumbnail" << std::endl;
}
outCurve = { DCT_Linear };
ProcParams neutral;
std::unique_ptr<IImage8> target;
{
int tr = TR_NONE;
int fw, fh;
getFullSize(fw, fh, tr);
int skip = 10;
PreviewProps pp(0, 0, fw, fh, skip);
ColorTemp currWB = getWB();
std::unique_ptr<Imagefloat> image(new Imagefloat(int(fw / skip), int(fh / skip)));
getImage(currWB, tr, image.get(), pp, neutral.toneCurve, neutral.raw);
// this could probably be made faster -- ideally we would need to just
// perform the transformation from camera space to the output space
// (taking gamma into account), but I couldn't find anything
// ready-made, so for now this will do. Remember the famous quote:
// "premature optimization is the root of all evil" :-)
convertColorSpace(image.get(), neutral.icm, currWB);
ImProcFunctions ipf(&neutral);
LabImage tmplab(image->getWidth(), image->getHeight());
ipf.rgb2lab(*image, tmplab, neutral.icm.working);
image.reset(ipf.lab2rgbOut(&tmplab, 0, 0, tmplab.W, tmplab.H, neutral.icm));
target.reset(image->to8());
if (settings->verbose) {
std::cout << "histogram matching: generated neutral rendering" << std::endl;
}
}
std::unique_ptr<IImage8> source;
{
RawMetaDataLocation rml;
eSensorType sensor_type;
int w, h;
std::unique_ptr<Thumbnail> thumb(Thumbnail::loadQuickFromRaw(getFileName(), rml, sensor_type, w, h, 1, false, true));
if (!thumb) {
if (settings->verbose) {
std::cout << "histogram matching: no thumbnail found, generating a neutral curve" << std::endl;
}
return;
}
source.reset(thumb->quickProcessImage(neutral, target->getHeight(), TI_Nearest));
if (settings->verbose) {
std::cout << "histogram matching: extracted embedded thumbnail" << std::endl;
}
}
if (target->getWidth() != source->getWidth() || target->getHeight() != source->getHeight()) {
Image8 *tmp = new Image8(source->getWidth(), source->getHeight());
target->resizeImgTo(source->getWidth(), source->getHeight(), TI_Nearest, tmp);
target.reset(tmp);
}
std::vector<int> scdf = getCdf(*source);
std::vector<int> tcdf = getCdf(*target);
std::vector<int> mapping;
int j = 0;
for (size_t i = 0; i < tcdf.size(); ++i) {
j = findMatch(tcdf[i], scdf, j);
mapping.push_back(j);
}
mappingToCurve(mapping, outCurve);
if (settings->verbose) {
std::cout << "histogram matching: generated curve with " << outCurve.size()/2 << " control points" << std::endl;
}
}
} // namespace rtengine