352 lines
12 KiB
C++
352 lines
12 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 <https://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 <iostream>
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#include <queue>
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#include "guidedfilter.h"
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#include "improcfun.h"
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#include "procparams.h"
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#include "rt_algo.h"
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#include "rt_algo.h"
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#include "rt_math.h"
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#define BENCHMARK
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#include "StopWatch.h"
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extern Options options;
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namespace rtengine {
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namespace {
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int get_dark_channel(const array2D<float> &R, const array2D<float> &G, const array2D<float> &B, array2D<float> &dst, int patchsize, const float ambient[3], bool clip, bool multithread, float strength)
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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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#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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const int pH = min(y + patchsize, H);
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for (int x = 0; x < W; x += patchsize) {
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float val = RT_INFINITY_F;
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const int pW = min(x + patchsize, W);
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for (int xx = x; xx < pW; ++xx) {
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for (int yy = y; yy < pH; ++yy) {
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val = min(val, R[yy][xx] / ambient[0], G[yy][xx] / ambient[1], B[yy][xx] / ambient[2]);
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}
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}
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val = 1.f - strength * 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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}
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}
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return (W / patchsize + ((W % patchsize) > 0)) * (H / patchsize + ((H % patchsize) > 0));
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}
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int get_dark_channel_downsized(const array2D<float> &R, const array2D<float> &G, const array2D<float> &B, array2D<float> &dst, int patchsize, 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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#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 yy = y / patchsize;
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const int pH = min(y + patchsize, H);
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for (int x = 0, xx = 0; x < W; x += patchsize, ++xx) {
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float val = RT_INFINITY_F;
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const int pW = min(x + patchsize, W);
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for (int xp = x; xp < pW; ++xp) {
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for (int yp = y; yp < pH; ++yp) {
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val = min(val, R[yp][xp], G[yp][xp], B[yp][xp]);
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}
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}
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dst[yy][xx] = val;
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}
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}
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return (W / patchsize + ((W % patchsize) > 0)) * (H / patchsize + ((H % patchsize) > 0));
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}
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float estimate_ambient_light(const array2D<float> &R, const array2D<float> &G, const array2D<float> &B, const array2D<float> &dark, 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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float darklim = RT_INFINITY_F;
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{
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std::vector<float> p;
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for (int y = 0, yy = 0; y < H; y += patchsize, ++yy) {
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for (int x = 0, xx = 0; x < W; x += patchsize, ++xx) {
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if (!OOG(dark[yy][xx], 1.f - 1e-5f)) {
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p.push_back(dark[yy][xx]);
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}
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}
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}
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const int pos = p.size() * 0.95;
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std::nth_element(p.begin(), p.begin() + pos, p.end());
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darklim = p[pos];
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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, yy = 0; y < H; y += patchsize, ++yy) {
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for (int x = 0, xx = 0; x < W; x += patchsize, ++xx) {
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if (dark[yy][xx] >= darklim && !OOG(dark[yy][xx], 1.f)) {
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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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float bright_lim = RT_INFINITY_F;
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{
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std::vector<float> l;
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l.reserve(patches.size() * patchsize * patchsize);
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for (const auto &p : patches) {
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const int pW = min(p.first + patchsize, W);
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const int pH = 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_back(R[y][x] + G[y][x] + B[y][x]);
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}
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}
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}
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const int pos = l.size() * 0.95;
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std::nth_element(l.begin(), l.begin() + pos, l.end());
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bright_lim = l[pos];
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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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#ifdef _OPENMP
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#pragma omp parallel for schedule(dynamic) reduction(+:rr,gg,bb,n)
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#endif
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for (const auto &p : patches) {
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const int pW = min(p.first + patchsize, W);
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const int pH = 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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const float r = R[y][x];
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const float g = G[y][x];
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const float b = B[y][x];
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if (r + g + b >= bright_lim) {
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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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n = std::max(n, 1);
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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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// taken from darktable
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return darklim > 0 ? -1.125f * std::log(darklim) : std::log(std::numeric_limits<float>::max()) / 2;
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}
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void extract_channels(Imagefloat *img, 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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array2D<float> imgR(W, H, img->r.ptrs, ARRAY2D_BYREFERENCE);
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guidedFilter(imgR, imgR, r, radius, epsilon, multithread);
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array2D<float> imgG(W, H, img->g.ptrs, ARRAY2D_BYREFERENCE);
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guidedFilter(imgG, imgG, g, radius, epsilon, multithread);
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array2D<float> imgB(W, H, img->b.ptrs, ARRAY2D_BYREFERENCE);
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guidedFilter(imgB, imgB, 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 || params->dehaze.strength == 0.0) {
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return;
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}
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BENCHFUN
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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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const 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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array2D<float> dark(W, H);
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int patchsize = max(int(5 / scale), 2);
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float ambient[3];
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float max_t = 0.f;
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{
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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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extract_channels(img, R, G, B, patchsize, 1e-1, multiThread);
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patchsize = max(max(W, H) / 600, 2);
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array2D<float> darkDownsized(W / patchsize + 1, H / patchsize + 1);
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const int npatches = get_dark_channel_downsized(R, G, B, darkDownsized, patchsize, multiThread);
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max_t = estimate_ambient_light(R, G, B, darkDownsized, patchsize, npatches, ambient);
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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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<< 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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get_dark_channel(R, G, B, dark, patchsize, ambient, true, multiThread, strength);
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}
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const int radius = patchsize * 4;
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constexpr float epsilon = 1e-5f;
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{
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array2D<float> guideB(W, H, img->b.ptrs, ARRAY2D_BYREFERENCE);
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guidedFilter(guideB, dark, dark, radius, epsilon, multiThread);
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}
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if (options.rtSettings.verbose) {
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std::cout << "dehaze: max distance is " << max_t << std::endl;
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}
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const float depth = -float(params->dehaze.depth) / 100.f;
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const float t0 = max(1e-3f, std::exp(depth * max_t));
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const float teps = 1e-3f;
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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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int x = 0;
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#ifdef __SSE2__
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const vfloat onev = F2V(1.f);
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const vfloat ambient0v = F2V(ambient[0]);
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const vfloat ambient1v = F2V(ambient[1]);
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const vfloat ambient2v = F2V(ambient[2]);
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const vfloat t0v = F2V(t0);
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const vfloat tepsv = F2V(teps);
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const vfloat c65535v = F2V(65535.f);
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for (; x < W - 3; x += 4) {
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// ensure that the transmission is such that to avoid clipping...
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vfloat r = LVFU(img->r(y, x));
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vfloat g = LVFU(img->g(y, x));
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vfloat b = LVFU(img->b(y, x));
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// ... t >= tl to avoid negative values
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const vfloat tlv = onev - vminf(r / ambient0v, vminf(g / ambient1v, b / ambient2v));
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// ... t >= tu to avoid values > 1
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r -= ambient0v;
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g -= ambient1v;
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b -= ambient2v;
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vfloat tuv = t0v - tepsv;
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tuv = vself(vmaskf_lt(ambient0v, onev), vmaxf(tuv, r / (onev - ambient0v)), tuv);
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tuv = vself(vmaskf_lt(ambient1v, onev), vmaxf(tuv, g / (onev - ambient1v)), tuv);
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tuv = vself(vmaskf_lt(ambient2v, onev), vmaxf(tuv, b / (onev - ambient2v)), tuv);
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const vfloat mtv = vmaxf(LVFU(dark[y][x]), vmaxf(tlv, tuv) + tepsv);
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if (params->dehaze.showDepthMap) {
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const vfloat valv = vclampf(onev - mtv, ZEROV, onev) * c65535v;
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STVFU(img->r(y, x), valv);
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STVFU(img->g(y, x), valv);
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STVFU(img->b(y, x), valv);
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} else {
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STVFU(img->r(y, x), (r / mtv + ambient0v) * c65535v);
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STVFU(img->g(y, x), (g / mtv + ambient1v) * c65535v);
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STVFU(img->b(y, x), (b / mtv + ambient2v) * c65535v);
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}
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}
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#endif
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for (; x < W; ++x) {
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// ensure that the transmission is such that to avoid clipping...
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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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// ... t >= tl to avoid negative values
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const float tl = 1.f - min(r / ambient[0], g / ambient[1], b / ambient[2]);
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// ... t >= tu to avoid values > 1
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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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float tu = t0 - teps;
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tu = ambient[0] < 1.f ? max(tu, r / (1.f - ambient[0])) : tu;
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tu = ambient[1] < 1.f ? max(tu, g / (1.f - ambient[1])) : tu;
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tu = ambient[2] < 1.f ? max(tu, b / (1.f - ambient[2])) : tu;
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const float mt = max(dark[y][x], tl + teps, tu + teps);
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if (params->dehaze.showDepthMap) {
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img->r(y, x) = img->g(y, x) = img->b(y, x) = LIM01(1.f - mt) * 65535.f;
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} else {
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img->r(y, x) = (r / mt + ambient[0]) * 65535.f;
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img->g(y, x) = (g / mt + ambient[1]) * 65535.f;
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img->b(y, x) = (b / mt + ambient[2]) * 65535.f;
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}
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}
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}
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}
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} // namespace rtengine
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