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Update AutoLevelAndAutoContrast
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‎AutoLevelAndAutoContrast.cpp‎

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#include "opencv2/opencv.hpp"
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#include "iostream"
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#include "algorithm"
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#include "vector"
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using namespace std;
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using namespace cv;
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Mat AutoLevel(Mat src, double LowCut, double HighCut){
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int rows = src.rows;
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int cols = src.cols;
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int totalPixel = rows * cols;
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//统计每个通道的直方图
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uchar Pixel[256*3] = {0};
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vector <Mat> rgb;
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split(src, rgb);
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Mat HistBlue, HistGreen, HistRed;
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int histSize = 256;
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float range[] = {0, 255};
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const float* histRange = {range};
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bool uniform = true;
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bool accumulate = false;
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calcHist(&rgb[0], 1, 0, Mat(), HistRed, 1, &histSize, &histRange, uniform, accumulate);
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calcHist(&rgb[1], 1, 0, Mat(), HistGreen, 1, &histSize, &histRange, uniform, accumulate);
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calcHist(&rgb[2], 1, 0, Mat(), HistBlue, 1, &histSize, &histRange, uniform, accumulate);
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//分别计算各通道按照给定的参数所确定的上下限值
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int MinBlue = 0, MaxBlue = 0;
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int MinRed = 0, MaxRed = 0;
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int MinGreen = 0, MaxGreen = 0;
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//Blue Channel
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float sum = 0;
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sum = 0;
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for(int i = 0; i < 256; i++){
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sum += HistBlue.at<float>(i);
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if(sum >= totalPixel * LowCut * 0.01){
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MinBlue = i;
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break;
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}
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}
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sum = 0;
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for(int i = 255; i >= 0; i--){
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sum = sum + HistBlue.at<float>(i);
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if(sum >= totalPixel * HighCut * 0.01){
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MaxBlue = i;
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break;
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}
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}
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//Red channel
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for(int i = 0; i < 256; i++){
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sum += HistRed.at<float>(i);
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if(sum >= totalPixel * LowCut * 0.01){
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MinRed = i;
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break;
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}
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}
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sum = 0;
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for(int i = 255; i >= 0; i--){
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sum = sum + HistRed.at<float>(i);
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if(sum >= totalPixel * HighCut * 0.01){
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MaxRed = i;
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break;
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}
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}
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//Green channel
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sum = 0;
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for(int i = 0; i < 256; i++){
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sum += HistGreen.at<float>(i);
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if(sum >= totalPixel * LowCut * 0.01){
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MinGreen = i;
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break;
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}
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}
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sum = 0;
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for(int i = 255; i >= 0; i--){
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sum = sum + HistGreen.at<float>(i);
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if(sum >= totalPixel * HighCut * 0.01){
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MaxGreen = i;
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break;
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}
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}
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printf("%d %d %d %d %d %d\n", MinGreen, MaxGreen, MinBlue, MaxBlue, MinRed, MaxRed);
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//自动色阶：按照我们刚刚计算出的MinBlue/MaxBlue构建一个隐射表
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for(int i = 0; i < 256; i++){
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if(i <= MinBlue){
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Pixel[i*3+2] = 0;
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}else{
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if(i > MaxBlue){
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Pixel[i*3+2] = 255;
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}else{
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float temp = (float)(i - MinBlue) / (MaxBlue - MinBlue);
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Pixel[i*3+2] = (uchar)(temp*255);
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}
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}
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if(i <= MinGreen){
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Pixel[i*3+1] = 0;
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}else{
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if(i > MaxGreen){
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Pixel[i*3+1] = 255;
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}else{
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float temp = (float)(i - MinGreen) / (MaxGreen - MinGreen);
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Pixel[i*3+1] = (uchar)(temp*255);
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}
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}
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if(i <= MinRed){
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Pixel[i*3] = 0;
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}else{
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if(i > MaxRed){
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Pixel[i*3] = 255;
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}else{
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float temp = (float)(i - MinRed) / (MaxRed - MinRed);
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Pixel[i*3] = (uchar)(temp*255);
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}
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}
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}
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Mat dst;
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Mat TMP(1, 256, CV_8UC3, Pixel);
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LUT(src, TMP, dst);
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return dst;
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}
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Mat AutoContrast(Mat src, double LowCut, double HighCut){
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int rows = src.rows;
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int cols = src.cols;
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int totalPixel = rows * cols;
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//统计每个通道的直方图
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uchar Pixel[256*3] = {0};
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vector <Mat> rgb;
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split(src, rgb);
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Mat HistBlue, HistGreen, HistRed;
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int histSize = 256;
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float range[] = {0, 255};
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const float* histRange = {range};
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bool uniform = true;
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bool accumulate = false;
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calcHist(&rgb[0], 1, 0, Mat(), HistRed, 1, &histSize, &histRange, uniform, accumulate);
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calcHist(&rgb[1], 1, 0, Mat(), HistGreen, 1, &histSize, &histRange, uniform, accumulate);
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calcHist(&rgb[2], 1, 0, Mat(), HistBlue, 1, &histSize, &histRange, uniform, accumulate);
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//分别计算各通道按照给定的参数所确定的上下限值
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int MinBlue = 0, MaxBlue = 0;
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int MinRed = 0, MaxRed = 0;
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int MinGreen = 0, MaxGreen = 0;
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//Blue Channel
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float sum = 0;
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sum = 0;
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for(int i = 0; i < 256; i++){
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sum += HistBlue.at<float>(i);
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if(sum >= totalPixel * LowCut * 0.01){
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MinBlue = i;
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break;
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}
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}
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sum = 0;
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for(int i = 255; i >= 0; i--){
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sum = sum + HistBlue.at<float>(i);
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if(sum >= totalPixel * HighCut * 0.01){
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MaxBlue = i;
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break;
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}
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}
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//Red channel
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for(int i = 0; i < 256; i++){
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sum += HistRed.at<float>(i);
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if(sum >= totalPixel * LowCut * 0.01){
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MinRed = i;
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break;
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}
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}
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sum = 0;
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for(int i = 255; i >= 0; i--){
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sum = sum + HistRed.at<float>(i);
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if(sum >= totalPixel * HighCut * 0.01){
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MaxRed = i;
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break;
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}
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}
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//Green channel
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sum = 0;
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for(int i = 0; i < 256; i++){
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sum += HistGreen.at<float>(i);
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if(sum >= totalPixel * LowCut * 0.01){
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MinGreen = i;
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break;
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}
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}
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sum = 0;
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for(int i = 255; i >= 0; i--){
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sum = sum + HistGreen.at<float>(i);
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if(sum >= totalPixel * HighCut * 0.01){
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MaxGreen = i;
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break;
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}
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}
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int minn = min(MinBlue, min(MinGreen, MinRed));
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int maxx = max(MaxBlue, max(MaxGreen, MaxRed));
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//自动对比度
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for(int i = 0; i < 256; i++){
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if(i <= minn){
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Pixel[i*3+2] = 0;
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}else{
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if(i > maxx){
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Pixel[i*3+2] = 255;
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}else{
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float temp = (float)(i - minn) / (maxx - minn);
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Pixel[i*3+2] = (uchar)(temp*255);
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}
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}
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if(i <= minn){
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Pixel[i*3+1] = 0;
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}else{
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if(i > maxx){
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Pixel[i*3+1] = 255;
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}else{
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float temp = (float)(i - minn) / (maxx - minn);
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Pixel[i*3+1] = (uchar)(temp*255);
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}
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}
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if(i <= minn){
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Pixel[i*3] = 0;
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}else{
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if(i > maxx){
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Pixel[i*3] = 255;
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}else{
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float temp = (float)(i - minn) / (maxx - minn);
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Pixel[i*3] = (uchar)(temp*255);
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}
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}
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}
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Mat dst;
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Mat TMP(1, 256, CV_8UC3, Pixel);
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LUT(src, TMP, dst);
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return dst;
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}
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int main(){
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Mat src = imread("../3.png");
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Mat dst = AutoLevel(src, 0.005, 0.005);
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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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- Local Color Correction.cpp C++复现了《Local Color Correction》论文，详情请参考：https://blog.csdn.net/just_sort/article/details/84539295
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- PartialcolorJudge.cpp C++复现了《基于图像分析的偏色检测及颜色校正方法》论文，实现快速判断图片是否存在偏色，详情请看：https://blog.csdn.net/just_sort/article/details/84897976
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- Optimized contrast enhancement for real-time image and video dehazin.cpp 复现了《Optimized contrast enhancement for real-time image and video dehazin》这篇论文，相对于He Kaiming的暗通道去雾，对天空具有天然的免疫力。详情请看：https://blog.csdn.net/just_sort/article/details/84932848
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- AutoLevelAndAutoContrast.cpp C++复现了自动色阶调整和自动对比度调整，其中自动色阶调整可以用于去雾和水下图像恢复，算法原理请看：https://www.cnblogs.com/Imageshop/archive/2011/11/13/2247614.html
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# ImageFiletering实现了各种滤波算法
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