本文代码来自于下面这篇博文：
https://blog.csdn.net/matt45m/article/details/104673585/
原文中只给出了函数，没有给出完整的可运行的代码。也没有说明第三个参数filter的意义和该取什么值。
实际跑了下，原文提供的函数一点问题没有，并且实测把filter的值置为1，可实现博文中的运行效果。
完整代码如下：
代码中用到的图像如下：
#include <opencv2/opencv.hpp>
#include <iostream>
using namespace cv;
using namespace std;
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void colorEnhancement(cv::Mat &src, cv::Mat &dst, int filter)
{
cv::Mat orig_img = src.clone();
cv::Mat simg;
if (orig_img.channels() != 1)
{
cvtColor(orig_img, simg, CV_BGR2GRAY);
}
else
{
return;
}
long int N = simg.rows*simg.cols;
int histo_b[256];
int histo_g[256];
int histo_r[256];
for (int i = 0; i<256; i++)
{
histo_b[i] = 0;
histo_g[i] = 0;
histo_r[i] = 0;
}
cv::Vec3b intensity;
for (int i = 0; i<simg.rows; i++)
{
for (int j = 0; j<simg.cols; j++)
{
intensity = orig_img.at<cv::Vec3b>(i, j);
histo_b[intensity.val[0]] = histo_b[intensity.val[0]] + 1;
histo_g[intensity.val[1]] = histo_g[intensity.val[1]] + 1;
histo_r[intensity.val[2]] = histo_r[intensity.val[2]] + 1;
}
}
for (int i = 1; i<256; i++)
{
histo_b[i] = histo_b[i] + filter * histo_b[i - 1];
histo_g[i] = histo_g[i] + filter * histo_g[i - 1];
histo_r[i] = histo_r[i] + filter * histo_r[i - 1];
}
int vmin_b = 0;
int vmin_g = 0;
int vmin_r = 0;
int s1 = 3;
int s2 = 3;
while (histo_b[vmin_b + 1] <= N*s1 / 100)
{
vmin_b = vmin_b + 1;
}
while (histo_g[vmin_g + 1] <= N*s1 / 100)
{
vmin_g = vmin_g + 1;
}
while (histo_r[vmin_r + 1] <= N*s1 / 100)
{
vmin_r = vmin_r + 1;
}
int vmax_b = 255 - 1;
int vmax_g = 255 - 1;
int vmax_r = 255 - 1;
while (histo_b[vmax_b - 1]>(N - ((N / 100)*s2)))
{
vmax_b = vmax_b - 1;
}
if (vmax_b < 255 - 1)
{
vmax_b = vmax_b + 1;
}
while (histo_g[vmax_g - 1]>(N - ((N / 100)*s2)))
{
vmax_g = vmax_g - 1;
}
if (vmax_g < 255 - 1)
{
vmax_g = vmax_g + 1;
}
while (histo_r[vmax_r - 1]>(N - ((N / 100)*s2)))
{
vmax_r = vmax_r - 1;
}
if (vmax_r < 255 - 1)
{
vmax_r = vmax_r + 1;
}
for (int i = 0; i<simg.rows; i++)
{
for (int j = 0; j<simg.cols; j++)
{
intensity = orig_img.at<cv::Vec3b>(i, j);
if (intensity.val[0]<vmin_b)
{
intensity.val[0] = vmin_b;
}
if (intensity.val[0]>vmax_b)
{
intensity.val[0] = vmax_b;
}
if (intensity.val[1]<vmin_g)
{
intensity.val[1] = vmin_g;
}
if (intensity.val[1]>vmax_g)
{
intensity.val[1] = vmax_g;
}
if (intensity.val[2]<vmin_r)
{
intensity.val[2] = vmin_r;
}
if (intensity.val[2]>vmax_r)
{
intensity.val[2] = vmax_r;
}
orig_img.at<cv::Vec3b>(i, j) = intensity;
}
}
for (int i = 0; i<simg.rows; i++)
{
for (int j = 0; j<simg.cols; j++)
{
intensity = orig_img.at<cv::Vec3b>(i, j);
intensity.val[0] = (intensity.val[0] - vmin_b) * 255 / (vmax_b - vmin_b);
intensity.val[1] = (intensity.val[1] - vmin_g) * 255 / (vmax_g - vmin_g);
intensity.val[2] = (intensity.val[2] - vmin_r) * 255 / (vmax_r - vmin_r);
orig_img.at<cv::Vec3b>(i, j) = intensity;
}
}
cv::Mat blurred;
double sigma = 1;
double threshold = 50;
double amount = 1;
GaussianBlur(orig_img, blurred, cv::Size(), sigma, sigma);
cv::Mat lowContrastMask = abs(orig_img - blurred) < threshold;
cv::Mat sharpened = orig_img*(1 + amount) + blurred*(-amount);
orig_img.copyTo(sharpened, lowContrastMask);
dst = sharpened.clone();
}
int main()
{
Mat src_image = imread("F:/material/images/2022/2022-06/gufeng1.jpg");
if (src_image.empty())
{
std::cout << "Error: Could not load image" << std::endl;
return 0;
}
imshow("Source Image", src_image);
Mat dst_image;
int filter = 1;
colorEnhancement(src_image, dst_image, filter);
imshow("dst_image", dst_image);
waitKey();
return(0);
}
运行结果如下：
至于原理，以后有需要的时候再探究吧！