Files
rawTherapee/rtengine/ipdehaze.cc
2018-10-12 16:01:48 +02:00

449 lines
14 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/>.
*/
/*
* Haze removal using the algorithm described in the paper:
*
* Single Image Haze Removal Using Dark Channel Prior
* by He, Sun and Tang
*
* using a guided filter for the "soft matting" of the transmission map
*
*/
#include "improcfun.h"
#include "guidedfilter.h"
#include "rt_math.h"
#include "rt_algo.h"
#include <iostream>
#include <queue>
extern Options options;
namespace rtengine {
namespace {
#if 0
# define DEBUG_DUMP(arr) \
do { \
Imagefloat im(arr.width(), arr.height()); \
const char *out = "/tmp/" #arr ".tif"; \
for (int y = 0; y < im.getHeight(); ++y) { \
for (int x = 0; x < im.getWidth(); ++x) { \
im.r(y, x) = im.g(y, x) = im.b(y, x) = arr[y][x] * 65535.f; \
} \
} \
im.saveTIFF(out, 16); \
} while (false)
#else
# define DEBUG_DUMP(arr)
#endif
int get_dark_channel(const array2D<float> &R, const array2D<float> &G, const array2D<float> &B, array2D<float> &dst,
int patchsize, float *ambient, bool multithread)
{
const int W = R.width();
const int H = R.height();
int npatches = 0;
#ifdef _OPENMP
#pragma omp parallel for if (multithread)
#endif
for (int y = 0; y < H; y += patchsize) {
int pH = std::min(y+patchsize, H);
for (int x = 0; x < W; x += patchsize, ++npatches) {
float val = RT_INFINITY_F;
int pW = std::min(x+patchsize, W);
for (int yy = y; yy < pH; ++yy) {
float yval = RT_INFINITY_F;
for (int xx = x; xx < pW; ++xx) {
float r = R[yy][xx];
float g = G[yy][xx];
float b = B[yy][xx];
if (ambient) {
r /= ambient[0];
g /= ambient[1];
b /= ambient[2];
}
yval = min(yval, r, g, b);
}
val = min(val, yval);
}
val = LIM01(val);
for (int yy = y; yy < pH; ++yy) {
std::fill(dst[yy]+x, dst[yy]+pW, val);
}
float val2 = RT_INFINITY_F;
for (int yy = y; yy < pH; ++yy) {
for (int xx = x; xx < pW; ++xx) {
float r = R[yy][xx];
float g = G[yy][xx];
float b = B[yy][xx];
if (ambient) {
r /= ambient[0];
g /= ambient[1];
b /= ambient[2];
}
float l = min(r, g, b);
if (l >= 2.f * val) {
val2 = min(val2, l);
dst[yy][xx] = -1;
}
}
}
if (val2 < RT_INFINITY_F) {
val2 = LIM01(val2);
for (int yy = y; yy < pH; ++yy) {
for (int xx = x; xx < pW; ++xx) {
if (dst[yy][xx] < 0.f) {
dst[yy][xx] = val2;
}
}
}
}
}
}
return npatches;
}
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])
{
const int W = R.width();
const int H = R.height();
const auto get_percentile =
[](std::priority_queue<float> &q, float prcnt) -> float
{
size_t n = LIM<size_t>(q.size() * prcnt, 1, q.size());
while (q.size() > n) {
q.pop();
}
return q.top();
};
float lim = RT_INFINITY_F;
{
std::priority_queue<float> p;
for (int y = 0; y < H; y += patchsize) {
for (int x = 0; x < W; x += patchsize) {
p.push(dark[y][x]);
}
}
lim = get_percentile(p, 0.95);
}
std::vector<std::pair<int, int>> patches;
patches.reserve(npatches);
for (int y = 0; y < H; y += patchsize) {
for (int x = 0; x < W; x += patchsize) {
if (dark[y][x] >= lim) {
patches.push_back(std::make_pair(x, y));
}
}
}
if (options.rtSettings.verbose) {
std::cout << "dehaze: computing ambient light from " << patches.size()
<< " patches" << std::endl;
}
{
std::priority_queue<float> l;
for (auto &p : patches) {
const int pW = std::min(p.first+patchsize, W);
const int pH = std::min(p.second+patchsize, H);
for (int y = p.second; y < pH; ++y) {
for (int x = p.first; x < pW; ++x) {
l.push(Y[y][x]);
}
}
}
lim = get_percentile(l, 0.95);
}
double rr = 0, gg = 0, bb = 0;
int n = 0;
for (auto &p : patches) {
const int pW = std::min(p.first+patchsize, W);
const int pH = std::min(p.second+patchsize, H);
for (int y = p.second; y < pH; ++y) {
for (int x = p.first; x < pW; ++x) {
if (Y[y][x] >= lim) {
float r = R[y][x];
float g = G[y][x];
float b = B[y][x];
rr += r;
gg += g;
bb += b;
++n;
}
}
}
}
ambient[0] = rr / n;
ambient[1] = gg / n;
ambient[2] = bb / n;
return n;
}
void get_luminance(Imagefloat *img, array2D<float> &Y, TMatrix ws, bool multithread)
{
const int W = img->getWidth();
const int H = img->getHeight();
#ifdef _OPENMP
#pragma omp parallel for if (multithread)
#endif
for (int y = 0; y < H; ++y) {
for (int x = 0; x < W; ++x) {
Y[y][x] = Color::rgbLuminance(img->r(y, x), img->g(y, x), img->b(y, x), ws);
}
}
}
void apply_contrast(array2D<float> &dark, float ambient, int contrast, double scale, bool multithread)
{
if (contrast) {
const int W = dark.width();
const int H = dark.height();
float avg = ambient * 0.25f;
float c = contrast * 0.3f;
std::vector<double> pts = {
DCT_NURBS,
0, //black point. Value in [0 ; 1] range
0, //black point. Value in [0 ; 1] range
avg - avg * (0.6 - c / 250.0), //toe point
avg - avg * (0.6 + c / 250.0), //value at toe point
avg + (1 - avg) * (0.6 - c / 250.0), //shoulder point
avg + (1 - avg) * (0.6 + c / 250.0), //value at shoulder point
1., // white point
1. // value at white point
};
const DiagonalCurve curve(pts, CURVES_MIN_POLY_POINTS / scale);
#ifdef _OPENMP
#pragma omp parallel for if (multithread)
#endif
for (int y = 0; y < H; ++y) {
for (int x = 0; x < W; ++x) {
dark[y][x] = curve.getVal(dark[y][x]);
}
}
}
}
void extract_channels(Imagefloat *img, const array2D<float> &Y, array2D<float> &r, array2D<float> &g, array2D<float> &b, int radius, float epsilon, bool multithread)
{
const int W = img->getWidth();
const int H = img->getHeight();
#ifdef _OPENMP
#pragma omp parallel for if (multithread)
#endif
for (int y = 0; y < H; ++y) {
for (int x = 0; x < W; ++x) {
r[y][x] = img->r(y, x);
g[y][x] = img->g(y, x);
b[y][x] = img->b(y, x);
}
}
guidedFilter(Y, r, r, radius, epsilon, multithread);
guidedFilter(Y, g, g, radius, epsilon, multithread);
guidedFilter(Y, b, b, radius, epsilon, multithread);
}
} // namespace
void ImProcFunctions::dehaze(Imagefloat *img)
{
if (!params->dehaze.enabled) {
return;
}
img->normalizeFloatTo1();
const int W = img->getWidth();
const int H = img->getHeight();
float strength = LIM01(float(params->dehaze.strength) / 100.f * 0.9f);
if (options.rtSettings.verbose) {
std::cout << "dehaze: strength = " << strength << std::endl;
}
TMatrix ws = ICCStore::getInstance()->workingSpaceMatrix(params->icm.workingProfile);
array2D<float> Y(W, H);
get_luminance(img, Y, ws, multiThread);
array2D<float> R(W, H);
array2D<float> G(W, H);
array2D<float> B(W, H);
int patchsize = max(int(20 / scale), 2);
extract_channels(img, Y, R, G, B, patchsize, 1e-1, multiThread);
array2D<float> dark(W, H);
patchsize = std::max(W / (200 + params->dehaze.detail * (SGN(params->dehaze.detail) > 0 ? 4 : 1)), 2);
int npatches = get_dark_channel(R, G, B, dark, patchsize, nullptr, multiThread);
DEBUG_DUMP(dark);
float ambient[3];
int n = estimate_ambient_light(R, G, B, dark, Y, patchsize, npatches, ambient);
float ambient_Y = Color::rgbLuminance(ambient[0], ambient[1], ambient[2], ws);
if (options.rtSettings.verbose) {
std::cout << "dehaze: ambient light is "
<< ambient[0] << ", " << ambient[1] << ", " << ambient[2]
<< " (average of " << n << ")"
<< std::endl;
std::cout << " ambient luminance is " << ambient_Y << std::endl;
}
if (min(ambient[0], ambient[1], ambient[2]) < 0.01f) {
if (options.rtSettings.verbose) {
std::cout << "dehaze: no haze detected" << std::endl;
}
img->normalizeFloatTo65535();
return; // probably no haze at all
}
array2D<float> &t_tilde = dark;
get_dark_channel(R, G, B, dark, patchsize, ambient, multiThread);
apply_contrast(dark, ambient_Y, params->dehaze.depth, scale, multiThread);
DEBUG_DUMP(t_tilde);
if (!params->dehaze.showDepthMap) {
#ifdef _OPENMP
#pragma omp parallel for if (multiThread)
#endif
for (int y = 0; y < H; ++y) {
for (int x = 0; x < W; ++x) {
dark[y][x] = 1.f - strength * dark[y][x];
}
}
}
float mult = 2.f;
if (params->dehaze.detail > 0) {
mult -= (params->dehaze.detail / 100.f) * 1.9f;
} else {
mult -= params->dehaze.detail / 10.f;
}
const int radius = max(int(patchsize * mult), 1);
const float epsilon = 2.5e-4;
array2D<float> &t = t_tilde;
if (!params->dehaze.showDepthMap)
guidedFilter(Y, t_tilde, t, radius, epsilon, multiThread);
DEBUG_DUMP(t);
if (params->dehaze.showDepthMap) {
#ifdef _OPENMP
#pragma omp parallel for if (multiThread)
#endif
for (int y = 0; y < H; ++y) {
for (int x = 0; x < W; ++x) {
img->r(y, x) = img->g(y, x) = img->b(y, x) = t[y][x] * 65535.f;
}
}
return;
}
const float t0 = 0.1;
const float teps = 1e-3;
#ifdef _OPENMP
#pragma omp parallel for if (multiThread)
#endif
for (int y = 0; y < H; ++y) {
for (int x = 0; x < W; ++x) {
float rgb[3] = { img->r(y, x), img->g(y, x), img->b(y, x) };
float tl = 1.f - min(rgb[0]/ambient[0], rgb[1]/ambient[1], rgb[2]/ambient[2]);
float tu = t0 - teps;
for (int c = 0; c < 3; ++c) {
if (ambient[c] < 1) {
tu = max(tu, (rgb[c] - ambient[c])/(1.f - ambient[c]));
}
}
float mt = max(t[y][x], t0, tl + teps, tu + teps);
float r = (rgb[0] - ambient[0]) / mt + ambient[0];
float g = (rgb[1] - ambient[1]) / mt + ambient[1];
float b = (rgb[2] - ambient[2]) / mt + ambient[2];
img->r(y, x) = r;
img->g(y, x) = g;
img->b(y, x) = b;
}
}
float oldmed;
findMinMaxPercentile(Y, Y.width() * Y.height(), 0.5, oldmed, 0.5, oldmed, multiThread);
get_luminance(img, Y, ws, multiThread);
float newmed;
findMinMaxPercentile(Y, Y.width() * Y.height(), 0.5, newmed, 0.5, newmed, multiThread);
if (newmed > 1e-5f) {
const float f1 = oldmed / newmed;
const float f = f1 * 65535.f;
#ifdef _OPENMP
#pragma omp parallel for if (multiThread)
#endif
for (int y = 0; y < H; ++y) {
for (int x = 0; x < W; ++x) {
float r = img->r(y, x);
float g = img->g(y, x);
float b = img->b(y, x);
float h, s, l;
Color::rgb2hslfloat(r * f, g * f, b * f, h, s, l);
s = LIM01(s / f1);
Color::hsl2rgbfloat(h, s, l, img->r(y, x), img->g(y, x), img->b(y, x));
}
}
} else {
img->normalizeFloatTo65535();
}
}
} // namespace rtengine