boost/gil/image_processing/histogram_equalization.hpp
//
// Copyright 2020 Debabrata Mandal <mandaldebabrata123@gmail.com>
//
// Use, modification and distribution are subject to the Boost Software License,
// Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt)
//
#ifndef BOOST_GIL_IMAGE_PROCESSING_HISTOGRAM_EQUALIZATION_HPP
#define BOOST_GIL_IMAGE_PROCESSING_HISTOGRAM_EQUALIZATION_HPP
#include <boost/gil/histogram.hpp>
#include <boost/gil/image.hpp>
#include <cmath>
#include <map>
#include <vector>
namespace boost { namespace gil {
/////////////////////////////////////////
/// Histogram Equalization(HE)
/////////////////////////////////////////
/// \defgroup HE HE
/// \brief Contains implementation and description of the algorithm used to compute
/// global histogram equalization of input images.
///
/// Algorithm :-
/// 1. If histogram A is to be equalized compute the cumulative histogram of A.
/// 2. Let CFD(A) refer to the cumulative histogram of A
/// 3. For a uniform histogram A', CDF(A') = A'
/// 4. We need to transfrom A to A' such that
/// 5. CDF(A') = CDF(A) => A' = CDF(A)
/// 6. Hence the pixel transform , px => histogram_of_ith_channel[px].
///
/// \fn histogram_equalization
/// \ingroup HE
/// \tparam SrcKeyType Key Type of input histogram
/// @param src_hist INPUT Input source histogram
/// \brief Overload for histogram equalization algorithm, takes in a single source histogram
/// and returns the color map used for histogram equalization.
///
template <typename SrcKeyType>
auto histogram_equalization(histogram<SrcKeyType> const& src_hist)
-> std::map<SrcKeyType, SrcKeyType>
{
histogram<SrcKeyType> dst_hist;
return histogram_equalization(src_hist, dst_hist);
}
/// \overload histogram_equalization
/// \ingroup HE
/// \tparam SrcKeyType Key Type of input histogram
/// \tparam DstKeyType Key Type of output histogram
/// @param src_hist INPUT source histogram
/// @param dst_hist OUTPUT Output histogram
/// \brief Overload for histogram equalization algorithm, takes in both source histogram &
/// destination histogram and returns the color map used for histogram equalization
/// as well as transforming the destination histogram.
///
template <typename SrcKeyType, typename DstKeyType>
auto histogram_equalization(histogram<SrcKeyType> const& src_hist, histogram<DstKeyType>& dst_hist)
-> std::map<SrcKeyType, DstKeyType>
{
static_assert(
std::is_integral<SrcKeyType>::value &&
std::is_integral<DstKeyType>::value,
"Source and destination histogram types are not appropriate");
using value_t = typename histogram<SrcKeyType>::value_type;
dst_hist.clear();
double sum = src_hist.sum();
SrcKeyType min_key = (std::numeric_limits<DstKeyType>::min)();
SrcKeyType max_key = (std::numeric_limits<DstKeyType>::max)();
auto cumltv_srchist = cumulative_histogram(src_hist);
std::map<SrcKeyType, DstKeyType> color_map;
std::for_each(cumltv_srchist.begin(), cumltv_srchist.end(), [&](value_t const& v) {
DstKeyType trnsfrmd_key =
static_cast<DstKeyType>((v.second * (max_key - min_key)) / sum + min_key);
color_map[std::get<0>(v.first)] = trnsfrmd_key;
});
std::for_each(src_hist.begin(), src_hist.end(), [&](value_t const& v) {
dst_hist[color_map[std::get<0>(v.first)]] += v.second;
});
return color_map;
}
/// \overload histogram_equalization
/// \ingroup HE
/// @param src_view INPUT source image view
/// @param dst_view OUTPUT Output image view
/// @param bin_width INPUT Histogram bin width
/// @param mask INPUT Specify is mask is to be used
/// @param src_mask INPUT Mask vector over input image
/// \brief Overload for histogram equalization algorithm, takes in both source & destination
/// image views and histogram equalizes the input image.
///
template <typename SrcView, typename DstView>
void histogram_equalization(
SrcView const& src_view,
DstView const& dst_view,
std::size_t bin_width = 1,
bool mask = false,
std::vector<std::vector<bool>> src_mask = {})
{
gil_function_requires<ImageViewConcept<SrcView>>();
gil_function_requires<MutableImageViewConcept<DstView>>();
static_assert(
color_spaces_are_compatible<
typename color_space_type<SrcView>::type,
typename color_space_type<DstView>::type>::value,
"Source and destination views must have same color space");
// Defining channel type
using source_channel_t = typename channel_type<SrcView>::type;
using dst_channel_t = typename channel_type<DstView>::type;
using coord_t = typename SrcView::x_coord_t;
std::size_t const channels = num_channels<SrcView>::value;
coord_t const width = src_view.width();
coord_t const height = src_view.height();
std::size_t pixel_max = (std::numeric_limits<dst_channel_t>::max)();
std::size_t pixel_min = (std::numeric_limits<dst_channel_t>::min)();
for (std::size_t i = 0; i < channels; i++)
{
histogram<source_channel_t> h;
fill_histogram(nth_channel_view(src_view, i), h, bin_width, false, false, mask, src_mask);
h.normalize();
auto h2 = cumulative_histogram(h);
for (std::ptrdiff_t src_y = 0; src_y < height; ++src_y)
{
auto src_it = nth_channel_view(src_view, i).row_begin(src_y);
auto dst_it = nth_channel_view(dst_view, i).row_begin(src_y);
for (std::ptrdiff_t src_x = 0; src_x < width; ++src_x)
{
if (mask && !src_mask[src_y][src_x])
dst_it[src_x][0] = channel_convert<dst_channel_t>(src_it[src_x][0]);
else
dst_it[src_x][0] = static_cast<dst_channel_t>(
h2[src_it[src_x][0]] * (pixel_max - pixel_min) + pixel_min);
}
}
}
}
}} //namespace boost::gil
#endif