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Add Automatic Color Equalization(ACE) and its Fast Implementation.cpp
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‎Automatic Color Equalization(ACE) and its Fast Implementation.cpp

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#include <stdio.h>
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#include <iostream>
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#include <immintrin.h>
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#include <opencv2/opencv.hpp>
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#include <opencv2/core/core.hpp>
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#include <opencv2/ml/ml.hpp>
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#include "opencv2/highgui/highgui.hpp"
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using namespace cv;
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using namespace cv::ml;
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using namespace std;
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namespace ACE {
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//Gray
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Mat stretchImage(Mat src) {
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int row = src.rows;
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int col = src.cols;
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Mat dst(row, col, CV_64FC1);
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double MaxValue = 0;
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double MinValue = 256.0;
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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MaxValue = max(MaxValue, src.at<double>(i, j));
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MinValue = min(MinValue, src.at<double>(i, j));
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}
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}
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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dst.at<double>(i, j) = (1.0 * src.at<double>(i, j) - MinValue) / (MaxValue - MinValue);
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if (dst.at<double>(i, j) > 1.0) {
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dst.at<double>(i, j) = 1.0;
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}
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else if (dst.at<double>(i, j) < 0) {
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dst.at<double>(i, j) = 0;
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}
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}
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}
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return dst;
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}
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Mat getPara(int radius) {
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int size = radius * 2 + 1;
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Mat dst(size, size, CV_64FC1);
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for (int i = -radius; i <= radius; i++) {
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for (int j = -radius; j <= radius; j++) {
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if (i == 0 && j == 0) {
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dst.at<double>(i + radius, j + radius) = 0;
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}
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else {
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dst.at<double>(i + radius, j + radius) = 1.0 / sqrt(i * i + j * j);
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}
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}
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}
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double sum = 0;
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for (int i = 0; i < size; i++) {
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for (int j = 0; j < size; j++) {
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sum += dst.at<double>(i, j);
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}
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}
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for (int i = 0; i < size; i++) {
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for (int j = 0; j < size; j++) {
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dst.at<double>(i, j) = dst.at<double>(i, j) / sum;
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}
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}
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return dst;
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}
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Mat NormalACE(Mat src, int ratio, int radius) {
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Mat para = getPara(radius);
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int row = src.rows;
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int col = src.cols;
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int size = 2 * radius + 1;
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Mat Z(row + 2 * radius, col + 2 * radius, CV_64FC1);
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for (int i = 0; i < Z.rows; i++) {
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for (int j = 0; j < Z.cols; j++) {
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if((i - radius >= 0) && (i - radius < row) && (j - radius >= 0) && (j - radius < col)) {
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Z.at<double>(i, j) = src.at<double>(i - radius, j - radius);
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}
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else {
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Z.at<double>(i, j) = 0;
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}
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}
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}
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Mat dst(row, col, CV_64FC1);
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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dst.at<double>(i, j) = 0.f;
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}
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}
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for (int i = 0; i < size; i++) {
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for (int j = 0; j < size; j++) {
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if (para.at<double>(i, j) == 0) continue;
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for (int x = 0; x < row; x++) {
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for (int y = 0; y < col; y++) {
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double sub = src.at<double>(x, y) - Z.at<double>(x + i, y + j);
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double tmp = sub * ratio;
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if (tmp > 1.0) tmp = 1.0;
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if (tmp < -1.0) tmp = -1.0;
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dst.at<double>(x, y) += tmp * para.at<double>(i, j);
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}
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}
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}
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}
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return dst;
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}
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Mat FastACE(Mat src, int ratio, int radius) {
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int row = src.rows;
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int col = src.cols;
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if (min(row, col) <= 2) {
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Mat dst(row, col, CV_64FC1);
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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dst.at<double>(i, j) = 0.5;
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}
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}
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return dst;
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}
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Mat Rs((row + 1) / 2, (col + 1) / 2, CV_64FC1);
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resize(src, Rs, Size((col + 1) / 2, (row + 1) / 2));
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Mat Rf= FastACE(Rs, ratio, radius);
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resize(Rf, Rf, Size(col, row));
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resize(Rs, Rs, Size(col, row));
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Mat dst(row, col, CV_64FC1);
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Mat dst1 = NormalACE(src, ratio, radius);
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Mat dst2 = NormalACE(Rs, ratio, radius);
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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dst.at<double>(i, j) = Rf.at<double>(i, j) + dst1.at<double>(i, j) - dst2.at<double>(i, j);
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}
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}
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return dst;
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}
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Mat getACE(Mat src, int ratio, int radius) {
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int row = src.rows;
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int col = src.cols;
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vector <Mat> v;
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split(src, v);
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v[0].convertTo(v[0], CV_64FC1);
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v[1].convertTo(v[1], CV_64FC1);
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v[2].convertTo(v[2], CV_64FC1);
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Mat src1(row, col, CV_64FC1);
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Mat src2(row, col, CV_64FC1);
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Mat src3(row, col, CV_64FC1);
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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src1.at<double>(i, j) = 1.0 * src.at<Vec3b>(i, j)[0] / 255.0;
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src2.at<double>(i, j) = 1.0 * src.at<Vec3b>(i, j)[1] / 255.0;
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src3.at<double>(i, j) = 1.0 * src.at<Vec3b>(i, j)[2] / 255.0;
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}
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}
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src1 = stretchImage(FastACE(src1, ratio, radius));
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src2 = stretchImage(FastACE(src2, ratio, radius));
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src3 = stretchImage(FastACE(src3, ratio, radius));
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Mat dst1(row, col, CV_8UC1);
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Mat dst2(row, col, CV_8UC1);
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Mat dst3(row, col, CV_8UC1);
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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dst1.at<uchar>(i, j) = (int)(src1.at<double>(i, j) * 255);
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if (dst1.at<uchar>(i, j) > 255) dst1.at<uchar>(i, j) = 255;
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else if (dst1.at<uchar>(i, j) < 0) dst1.at<uchar>(i, j) = 0;
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dst2.at<uchar>(i, j) = (int)(src2.at<double>(i, j) * 255);
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if (dst2.at<uchar>(i, j) > 255) dst2.at<uchar>(i, j) = 255;
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else if (dst2.at<uchar>(i, j) < 0) dst2.at<uchar>(i, j) = 0;
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dst3.at<uchar>(i, j) = (int)(src3.at<double>(i, j) * 255);
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if (dst3.at<uchar>(i, j) > 255) dst3.at<uchar>(i, j) = 255;
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else if (dst3.at<uchar>(i, j) < 0) dst3.at<uchar>(i, j) = 0;
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}
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}
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vector <Mat> out;
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out.push_back(dst1);
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out.push_back(dst2);
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out.push_back(dst3);
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Mat dst;
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merge(out, dst);
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return dst;
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}
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}
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using namespace ACE;
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int main() {
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Mat src = imread("F:\\sky.jpg");
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Mat dst = getACE(src, 4, 7);
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imshow("origin", src);
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imshow("result", dst);
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waitKey(0);
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}

‎README.md

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- Adaptive correction algorithm for illumination inhomogeneity image based on two-dimensional gamma function.cpp C++复现了《基于二维伽马函数的光照不均匀图像自适应校正算法》这篇论文，对光照不均匀的图像有较好的校正效果，且不会像Retiex那样出现光晕。原理请看：https://blog.csdn.net/just_sort/article/details/88569129
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- Real-time adaptive contrast enhancement for imaging sensors.cpp C++复现了《Real-time adaptive contrast enhancement for imaging sensors》这篇论文，实时自适应局部对比度增强算法。原理请看：https://blog.csdn.net/just_sort/article/details/85208124
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- AutomaticWhiteBalanceMethod.cpp C++复现了《A Novel Automatic White Balance Method For Digital Still Cameras》这篇论文，实现了效果比完美反射更好得白平衡效果。原理请看：https://blog.csdn.net/just_sort/article/details/89183909
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- Automatic Color Equalization(ACE) and its Fast Implementation.cpp C++复现了IPOL《Automatic Color Equalization(ACE) and its Fast Implementation》论文，用于自动色彩均衡。原理请看：https://blog.csdn.net/just_sort/article/details/85237711
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