449 lines
14 KiB
C++
449 lines
14 KiB
C++
/* -*- C++ -*-
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*
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* This file is part of RawTherapee.
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*
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* Copyright (c) 2018 Alberto Griggio <alberto.griggio@gmail.com>
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*
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* RawTherapee 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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* RawTherapee 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 RawTherapee. If not, see <http://www.gnu.org/licenses/>.
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*/
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/*
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* Haze removal using the algorithm described in the paper:
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*
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* Single Image Haze Removal Using Dark Channel Prior
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* by He, Sun and Tang
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*
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* using a guided filter for the "soft matting" of the transmission map
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*
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*/
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#include "improcfun.h"
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#include "guidedfilter.h"
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#include "rt_math.h"
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#include "rt_algo.h"
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#include <iostream>
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#include <queue>
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extern Options options;
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namespace rtengine {
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namespace {
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#if 0
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# define DEBUG_DUMP(arr) \
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do { \
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Imagefloat im(arr.width(), arr.height()); \
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const char *out = "/tmp/" #arr ".tif"; \
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for (int y = 0; y < im.getHeight(); ++y) { \
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for (int x = 0; x < im.getWidth(); ++x) { \
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im.r(y, x) = im.g(y, x) = im.b(y, x) = arr[y][x] * 65535.f; \
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} \
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} \
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im.saveTIFF(out, 16); \
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} while (false)
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#else
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# define DEBUG_DUMP(arr)
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#endif
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int get_dark_channel(const array2D<float> &R, const array2D<float> &G, const array2D<float> &B, array2D<float> &dst,
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int patchsize, float *ambient, bool multithread)
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{
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const int W = R.width();
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const int H = R.height();
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int npatches = 0;
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#ifdef _OPENMP
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#pragma omp parallel for if (multithread)
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#endif
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for (int y = 0; y < H; y += patchsize) {
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int pH = std::min(y+patchsize, H);
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for (int x = 0; x < W; x += patchsize, ++npatches) {
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float val = RT_INFINITY_F;
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int pW = std::min(x+patchsize, W);
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for (int yy = y; yy < pH; ++yy) {
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float yval = RT_INFINITY_F;
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for (int xx = x; xx < pW; ++xx) {
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float r = R[yy][xx];
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float g = G[yy][xx];
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float b = B[yy][xx];
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if (ambient) {
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r /= ambient[0];
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g /= ambient[1];
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b /= ambient[2];
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}
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yval = min(yval, r, g, b);
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}
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val = min(val, yval);
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}
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val = LIM01(val);
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for (int yy = y; yy < pH; ++yy) {
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std::fill(dst[yy]+x, dst[yy]+pW, val);
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}
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float val2 = RT_INFINITY_F;
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for (int yy = y; yy < pH; ++yy) {
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for (int xx = x; xx < pW; ++xx) {
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float r = R[yy][xx];
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float g = G[yy][xx];
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float b = B[yy][xx];
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if (ambient) {
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r /= ambient[0];
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g /= ambient[1];
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b /= ambient[2];
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}
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float l = min(r, g, b);
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if (l >= 2.f * val) {
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val2 = min(val2, l);
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dst[yy][xx] = -1;
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}
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}
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}
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if (val2 < RT_INFINITY_F) {
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val2 = LIM01(val2);
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for (int yy = y; yy < pH; ++yy) {
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for (int xx = x; xx < pW; ++xx) {
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if (dst[yy][xx] < 0.f) {
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dst[yy][xx] = val2;
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}
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}
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}
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}
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}
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}
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return npatches;
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}
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int estimate_ambient_light(const array2D<float> &R, const array2D<float> &G, const array2D<float> &B, const array2D<float> &dark, const array2D<float> &Y, int patchsize, int npatches, float ambient[3])
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{
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const int W = R.width();
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const int H = R.height();
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const auto get_percentile =
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[](std::priority_queue<float> &q, float prcnt) -> float
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{
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size_t n = LIM<size_t>(q.size() * prcnt, 1, q.size());
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while (q.size() > n) {
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q.pop();
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}
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return q.top();
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};
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float lim = RT_INFINITY_F;
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{
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std::priority_queue<float> p;
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for (int y = 0; y < H; y += patchsize) {
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for (int x = 0; x < W; x += patchsize) {
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p.push(dark[y][x]);
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}
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}
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lim = get_percentile(p, 0.95);
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}
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std::vector<std::pair<int, int>> patches;
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patches.reserve(npatches);
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for (int y = 0; y < H; y += patchsize) {
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for (int x = 0; x < W; x += patchsize) {
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if (dark[y][x] >= lim) {
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patches.push_back(std::make_pair(x, y));
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}
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}
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}
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if (options.rtSettings.verbose) {
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std::cout << "dehaze: computing ambient light from " << patches.size()
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<< " patches" << std::endl;
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}
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{
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std::priority_queue<float> l;
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for (auto &p : patches) {
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const int pW = std::min(p.first+patchsize, W);
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const int pH = std::min(p.second+patchsize, H);
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for (int y = p.second; y < pH; ++y) {
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for (int x = p.first; x < pW; ++x) {
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l.push(Y[y][x]);
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}
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}
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}
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lim = get_percentile(l, 0.95);
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}
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double rr = 0, gg = 0, bb = 0;
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int n = 0;
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for (auto &p : patches) {
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const int pW = std::min(p.first+patchsize, W);
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const int pH = std::min(p.second+patchsize, H);
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for (int y = p.second; y < pH; ++y) {
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for (int x = p.first; x < pW; ++x) {
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if (Y[y][x] >= lim) {
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float r = R[y][x];
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float g = G[y][x];
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float b = B[y][x];
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rr += r;
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gg += g;
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bb += b;
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++n;
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}
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}
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}
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}
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ambient[0] = rr / n;
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ambient[1] = gg / n;
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ambient[2] = bb / n;
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return n;
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}
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void get_luminance(Imagefloat *img, array2D<float> &Y, TMatrix ws, bool multithread)
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{
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const int W = img->getWidth();
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const int H = img->getHeight();
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#ifdef _OPENMP
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#pragma omp parallel for if (multithread)
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#endif
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for (int y = 0; y < H; ++y) {
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for (int x = 0; x < W; ++x) {
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Y[y][x] = Color::rgbLuminance(img->r(y, x), img->g(y, x), img->b(y, x), ws);
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}
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}
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}
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void apply_contrast(array2D<float> &dark, float ambient, int contrast, double scale, bool multithread)
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{
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if (contrast) {
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const int W = dark.width();
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const int H = dark.height();
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float avg = ambient * 0.25f;
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float c = contrast * 0.3f;
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std::vector<double> pts = {
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DCT_NURBS,
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0, //black point. Value in [0 ; 1] range
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0, //black point. Value in [0 ; 1] range
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avg - avg * (0.6 - c / 250.0), //toe point
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avg - avg * (0.6 + c / 250.0), //value at toe point
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avg + (1 - avg) * (0.6 - c / 250.0), //shoulder point
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avg + (1 - avg) * (0.6 + c / 250.0), //value at shoulder point
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1., // white point
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1. // value at white point
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};
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const DiagonalCurve curve(pts, CURVES_MIN_POLY_POINTS / scale);
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#ifdef _OPENMP
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#pragma omp parallel for if (multithread)
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#endif
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for (int y = 0; y < H; ++y) {
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for (int x = 0; x < W; ++x) {
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dark[y][x] = curve.getVal(dark[y][x]);
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}
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}
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}
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}
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void extract_channels(Imagefloat *img, const array2D<float> &Y, array2D<float> &r, array2D<float> &g, array2D<float> &b, int radius, float epsilon, bool multithread)
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{
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const int W = img->getWidth();
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const int H = img->getHeight();
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#ifdef _OPENMP
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#pragma omp parallel for if (multithread)
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#endif
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for (int y = 0; y < H; ++y) {
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for (int x = 0; x < W; ++x) {
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r[y][x] = img->r(y, x);
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g[y][x] = img->g(y, x);
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b[y][x] = img->b(y, x);
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}
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}
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guidedFilter(Y, r, r, radius, epsilon, multithread);
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guidedFilter(Y, g, g, radius, epsilon, multithread);
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guidedFilter(Y, b, b, radius, epsilon, multithread);
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}
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} // namespace
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void ImProcFunctions::dehaze(Imagefloat *img)
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{
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if (!params->dehaze.enabled) {
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return;
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}
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img->normalizeFloatTo1();
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const int W = img->getWidth();
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const int H = img->getHeight();
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float strength = LIM01(float(params->dehaze.strength) / 100.f * 0.9f);
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if (options.rtSettings.verbose) {
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std::cout << "dehaze: strength = " << strength << std::endl;
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}
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TMatrix ws = ICCStore::getInstance()->workingSpaceMatrix(params->icm.workingProfile);
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array2D<float> Y(W, H);
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get_luminance(img, Y, ws, multiThread);
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array2D<float> R(W, H);
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array2D<float> G(W, H);
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array2D<float> B(W, H);
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int patchsize = max(int(20 / scale), 2);
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extract_channels(img, Y, R, G, B, patchsize, 1e-1, multiThread);
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array2D<float> dark(W, H);
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patchsize = std::max(W / (200 + params->dehaze.detail * (SGN(params->dehaze.detail) > 0 ? 4 : 1)), 2);
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int npatches = get_dark_channel(R, G, B, dark, patchsize, nullptr, multiThread);
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DEBUG_DUMP(dark);
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float ambient[3];
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int n = estimate_ambient_light(R, G, B, dark, Y, patchsize, npatches, ambient);
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float ambient_Y = Color::rgbLuminance(ambient[0], ambient[1], ambient[2], ws);
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if (options.rtSettings.verbose) {
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std::cout << "dehaze: ambient light is "
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<< ambient[0] << ", " << ambient[1] << ", " << ambient[2]
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<< " (average of " << n << ")"
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<< std::endl;
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std::cout << " ambient luminance is " << ambient_Y << std::endl;
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}
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if (min(ambient[0], ambient[1], ambient[2]) < 0.01f) {
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if (options.rtSettings.verbose) {
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std::cout << "dehaze: no haze detected" << std::endl;
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}
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img->normalizeFloatTo65535();
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return; // probably no haze at all
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}
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array2D<float> &t_tilde = dark;
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get_dark_channel(R, G, B, dark, patchsize, ambient, multiThread);
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apply_contrast(dark, ambient_Y, params->dehaze.depth, scale, multiThread);
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DEBUG_DUMP(t_tilde);
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if (!params->dehaze.showDepthMap) {
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#ifdef _OPENMP
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#pragma omp parallel for if (multiThread)
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#endif
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for (int y = 0; y < H; ++y) {
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for (int x = 0; x < W; ++x) {
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dark[y][x] = 1.f - strength * dark[y][x];
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}
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}
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}
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float mult = 2.f;
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if (params->dehaze.detail > 0) {
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mult -= (params->dehaze.detail / 100.f) * 1.9f;
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} else {
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mult -= params->dehaze.detail / 10.f;
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}
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const int radius = max(int(patchsize * mult), 1);
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const float epsilon = 2.5e-4;
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array2D<float> &t = t_tilde;
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if (!params->dehaze.showDepthMap)
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guidedFilter(Y, t_tilde, t, radius, epsilon, multiThread);
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DEBUG_DUMP(t);
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if (params->dehaze.showDepthMap) {
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#ifdef _OPENMP
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#pragma omp parallel for if (multiThread)
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#endif
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for (int y = 0; y < H; ++y) {
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for (int x = 0; x < W; ++x) {
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img->r(y, x) = img->g(y, x) = img->b(y, x) = t[y][x] * 65535.f;
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}
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}
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return;
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}
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const float t0 = 0.1;
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const float teps = 1e-3;
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#ifdef _OPENMP
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#pragma omp parallel for if (multiThread)
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#endif
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for (int y = 0; y < H; ++y) {
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for (int x = 0; x < W; ++x) {
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float rgb[3] = { img->r(y, x), img->g(y, x), img->b(y, x) };
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float tl = 1.f - min(rgb[0]/ambient[0], rgb[1]/ambient[1], rgb[2]/ambient[2]);
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float tu = t0 - teps;
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for (int c = 0; c < 3; ++c) {
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if (ambient[c] < 1) {
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tu = max(tu, (rgb[c] - ambient[c])/(1.f - ambient[c]));
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}
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}
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float mt = max(t[y][x], t0, tl + teps, tu + teps);
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float r = (rgb[0] - ambient[0]) / mt + ambient[0];
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float g = (rgb[1] - ambient[1]) / mt + ambient[1];
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float b = (rgb[2] - ambient[2]) / mt + ambient[2];
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img->r(y, x) = r;
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img->g(y, x) = g;
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img->b(y, x) = b;
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}
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}
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float oldmed;
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findMinMaxPercentile(Y, Y.width() * Y.height(), 0.5, oldmed, 0.5, oldmed, multiThread);
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get_luminance(img, Y, ws, multiThread);
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float newmed;
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findMinMaxPercentile(Y, Y.width() * Y.height(), 0.5, newmed, 0.5, newmed, multiThread);
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if (newmed > 1e-5f) {
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const float f1 = oldmed / newmed;
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const float f = f1 * 65535.f;
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#ifdef _OPENMP
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#pragma omp parallel for if (multiThread)
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#endif
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for (int y = 0; y < H; ++y) {
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for (int x = 0; x < W; ++x) {
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float r = img->r(y, x);
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float g = img->g(y, x);
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float b = img->b(y, x);
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float h, s, l;
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Color::rgb2hslfloat(r * f, g * f, b * f, h, s, l);
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s = LIM01(s / f1);
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Color::hsl2rgbfloat(h, s, l, img->r(y, x), img->g(y, x), img->b(y, x));
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}
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}
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} else {
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img->normalizeFloatTo65535();
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}
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}
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} // namespace rtengine
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