注:轉載請標明原文出處鏈接:https://xiongyiming.blog.csdn.net/article/details/106987593
圖像變換可以看作如下:
(1) 像素變換:點操作
(2) 鄰域操作:區域
調整圖像亮度和對比度屬於像素變換——點操作
其中, , 是增益變量。通過調整 的大小可以使圖像變亮 或 變暗。
(1) 當 ,圖像 變亮;
(2) 當 ,圖像 變暗;
代碼中重要部分的解釋:
(1) Mat new_image = Mat::zeros( image.size(), image.type() );
//創建和原圖像大小和類型一致的空白圖像, 像素值初始化爲0;
(2) saturate_cast<uchar>(value)
//確保值大小範圍爲0~255之間;
(3) Mat.at<Vec3b>(y, x)[index]=value;
//給每個像素點每個通道賦值;
代碼示例
#include <opencv2/core/core.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/highgui/highgui_c.h>
#include <iostream>
#include <math.h>
using namespace cv;
using namespace std;
int main(int argc, char** args)
{
Mat src = imread("ZXP1.jpg", IMREAD_UNCHANGED);
if (src.empty())
{
cout << "could not find the image resource..." << std::endl;
return -1;
}
namedWindow("Original Image", CV_WINDOW_AUTOSIZE);
imshow("Original Image", src);
int height = src.rows;
int width = src.cols;
Mat dst;
dst = Mat::zeros(src.size(), src.type());
float alpha = 1.2;
float beta = 30;
Mat m1;
src.convertTo(m1, CV_32F);
for (int row = 0; row < height; row++)
{
for (int col = 0; col < width; col++)
{
if (src.channels() == 3)
{
float b = m1.at<Vec3f>(row, col)[0];
float g = m1.at<Vec3f>(row, col)[1];
float r = m1.at<Vec3f>(row, col)[2];
dst.at<Vec3b>(row, col)[0] = saturate_cast<uchar>(b*alpha + beta);
dst.at<Vec3b>(row, col)[1] = saturate_cast<uchar>(g*alpha + beta);
dst.at<Vec3b>(row, col)[2] = saturate_cast<uchar>(r*alpha + beta);
}
else if (src.channels() == 1)
{
float v = src.at<uchar>(row, col);
dst.at<uchar>(row, col) = saturate_cast<uchar>(v*alpha + beta);
}
}
}
namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
imshow("Output Image", dst);
waitKey(0);
return 0;
}
運行結果
(1) alpha = 1.2; beta = 30; ——> 圖像變亮
(2) alpha = 0.8; beta = 30; ——> 圖像變暗
參考資料
[1] https://edu.51cto.com/course/7521.html?source=so