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138 lines
5.1 KiB
C++
138 lines
5.1 KiB
C++
//
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// Copyright 2020 Debabrata Mandal <mandaldebabrata123@gmail.com>
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//
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// Use, modification and distribution are subject to the Boost Software License,
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// Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at
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// http://www.boost.org/LICENSE_1_0.txt)
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//
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#include <boost/gil/image_view.hpp>
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#include <boost/gil/histogram.hpp>
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#include <boost/gil/color_base_algorithm.hpp>
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#include <boost/gil/image_processing/histogram_matching.hpp>
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#include <boost/gil/extension/toolbox/metafunctions/get_pixel_type.hpp>
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#include <boost/core/lightweight_test.hpp>
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#include <vector>
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#include <iostream>
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const int a = 5;
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const double epsilon = 0.000001; // Decided by the value 5/255 i.e. an error of 5 px in 255 px
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boost::gil::gray8_image_t original(a, a), reference(a, a);
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boost::gil::gray8_image_t processed(a, a), processed2(a, a);
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std::vector<std::vector<int> > test1_random{
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{ 1, 10, 10, 10, 10},
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{ 20, 25, 25, 55, 20},
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{ 0, 55, 55, 55, 20},
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{ 20, 255, 255, 255, 0},
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{ 100, 100, 100, 10, 0}};
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std::vector<std::vector<int> > test1_reference{
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{ 0, 10, 20, 30, 40},
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{ 50, 60, 70, 80, 90},
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{ 100, 110, 120, 130, 140},
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{ 150, 160, 170, 180, 190},
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{ 200, 210, 220, 230, 240}};
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std::vector<std::vector<int> > test2_uniform{
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{ 0, 10, 20, 30, 40},
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{ 50, 60, 70, 80, 90},
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{ 100, 110, 120, 130, 140},
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{ 150, 160, 170, 180, 190},
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{ 200, 210, 220, 230, 240}};
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std::vector<std::vector<int> > test2_reference{
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{ 10, 20, 30, 40, 51},
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{ 61, 71, 81, 91, 102},
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{ 112, 122, 132, 142, 153},
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{ 163, 173, 183, 193, 204},
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{ 214, 224, 234, 244, 255}};
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std::vector<std::vector<int> > test3_equal_image{
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{ 0, 10, 20, 30, 40},
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{ 50, 60, 70, 80, 90},
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{ 100, 110, 120, 130, 140},
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{ 150, 160, 170, 180, 190},
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{ 200, 210, 220, 230, 240}};
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std::vector<std::vector<int> > test3_reference{
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{ 0, 10, 20, 30, 40},
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{ 50, 60, 70, 80, 90},
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{ 100, 110, 120, 130, 140},
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{ 150, 160, 170, 180, 190},
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{ 200, 210, 220, 230, 240}};
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void vector_to_gray_image(boost::gil::gray8_image_t& img,
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std::vector<std::vector<int> >& grid)
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{
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for(std::ptrdiff_t y=0; y<grid.size(); ++y)
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{
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for(std::ptrdiff_t x=0; x<grid[0].size(); ++x)
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{
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boost::gil::view(img)(x,y) = boost::gil::gray8_pixel_t(grid[y][x]);
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}
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}
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}
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template<typename SrcView>
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bool equal_histograms(SrcView const& v1, SrcView const& v2, double threshold = epsilon)
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{
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double sum=0.0;
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using channel_t = typename boost::gil::channel_type<SrcView>::type;
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boost::gil::histogram<channel_t> h1, h2;
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using value_t = typename boost::gil::histogram<channel_t>::value_type;
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channel_t max_p = std::numeric_limits<channel_t>::max();
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channel_t min_p = std::numeric_limits<channel_t>::min();
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long int num_pixels = v1.width() * v1.height();
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boost::gil::fill_histogram(v1, h1, 1, false, false);
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boost::gil::fill_histogram(v2, h2, 1, false, false);
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auto ch1 = boost::gil::cumulative_histogram(h1);
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auto ch2 = boost::gil::cumulative_histogram(h2);
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std::for_each(ch1.begin(), ch1.end(), [&](value_t const& v) {
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sum+=abs(v.second-ch1[v.first]);
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});
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return ( abs(sum) / (ch1.size() * (max_p - min_p)) < threshold );
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}
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void test_random_image()
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{
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vector_to_gray_image(original,test1_random);
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vector_to_gray_image(reference,test1_reference);
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histogram_matching(boost::gil::const_view(original),boost::gil::const_view(reference),boost::gil::view(processed));
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BOOST_TEST(equal_histograms(boost::gil::view(processed), boost::gil::view(reference)));
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histogram_matching(boost::gil::const_view(processed),boost::gil::const_view(reference),boost::gil::view(processed2));
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BOOST_TEST(equal_histograms(boost::gil::view(processed), boost::gil::view(processed2)));
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}
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void test_uniform_image()
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{
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vector_to_gray_image(original,test2_uniform);
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vector_to_gray_image(reference,test2_reference);
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histogram_matching(boost::gil::const_view(original),boost::gil::const_view(reference),boost::gil::view(processed));
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BOOST_TEST(equal_histograms(boost::gil::view(processed), boost::gil::view(reference)));
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histogram_matching(boost::gil::const_view(processed),boost::gil::const_view(reference),boost::gil::view(processed2));
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BOOST_TEST(equal_histograms(boost::gil::view(processed), boost::gil::view(processed2)));
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}
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void test_equal_image()
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{
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vector_to_gray_image(original,test3_equal_image);
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vector_to_gray_image(reference,test3_reference);
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histogram_matching(boost::gil::const_view(original),boost::gil::const_view(reference),boost::gil::view(processed));
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BOOST_TEST(equal_histograms(boost::gil::view(processed), boost::gil::view(reference)));
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histogram_matching(boost::gil::const_view(processed),boost::gil::const_view(reference),boost::gil::view(processed2));
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BOOST_TEST(equal_histograms(boost::gil::view(processed), boost::gil::view(processed2)));
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}
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int main()
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{
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//Basic tests for grayscale histogram_equalization
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test_random_image();
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test_uniform_image();
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test_equal_image();
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return boost::report_errors();
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}
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