一.调整图像亮度与对比度
1.图像变换
---像素变换-点操作
---邻域操作-区域操作
调整图像亮度和对比度属于像素变换-点操作
公式为：g(i,j) = αf(i,j) + β 其中α>0 ,β是增益变量
处理图像经常会对图像色彩进行增强，这就是改变图像的亮度β和对比度α，
我们看看实例代码：
1 #include<opencv2opencv.hpp> 2 #include<iostream> 3 4 using namespace std; 5 using namespace cv; 6 /*图像操作*/ 7 int main(int argc, char **argv) 8 { 9 Mat src1 = imread("E:\vsprom\learn05\v15.jpg"); 10 11 if (src1.empty()) 12 { 13 cout << "can not load imagefile1...." << endl; 14 return -1; 15 } 16 namedWindow("in1 image win", CV_WINDOW_AUTOSIZE); 17 imshow("in1 image win", src1); 18 19 int height = src1.rows; 20 int width = src1.cols; 21 22 Mat dst = Mat::zeros(src1.size(), src1.type());//创建一副与src1同样的图像，并将像素值全部给0 23 float alpha = 1.2; 24 float beta = 30; 25 for (int row = 0; row < height; row++) 26 { 27 for (int col = 0; col < width; col++) 28 { 29 if (src1.channels() == 3)//三通道图像 30 { 31 float b = src1.at<Vec3b>(row, col)[0];//通道1 32 float g = src1.at<Vec3b>(row, col)[1];//通道2 33 float r = src1.at<Vec3b>(row, col)[2];//通道3 34 35 dst.at<Vec3b>(row, col)[0] = saturate_cast<uchar>(b*alpha + beta);//使用公式 36 dst.at<Vec3b>(row, col)[1] = saturate_cast<uchar>(g*alpha + beta); 37 dst.at<Vec3b>(row, col)[2] = saturate_cast<uchar>(r*alpha + beta); 38 39 } 40 else if (src1.channels() == 1)//单通道图像 41 { 42 float v = src1.at<uchar>(row, col); 43 dst.at<uchar>(row, col) = saturate_cast<uchar>(v*alpha + beta); 44 } 45 } 46 } 47 namedWindow("dst image win", CV_WINDOW_AUTOSIZE); 48 imshow("dst image win", dst); 49 50 51 waitKey(0); 52 return 0; 53 }
效果如下此时α=1.2，β=30
效果如下α=1.2，β=100时，此时更亮
效果如下α=5，β=30时,对比更明显
转换图像格式：
src2.convertTo(src1, CV_32F);
代码为：
#include<opencv2opencv.hpp> #include<iostream> using namespace std; using namespace cv; /*图像操作*/ int main(int argc, char **argv) { Mat src2 = imread("E:\vsprom\learn05\v15.jpg"); if (src2.empty()) { cout << "can not load imagefile1...." << endl; return -1; } namedWindow("in1 image win", CV_WINDOW_AUTOSIZE); imshow("in1 image win", src2); Mat src1; src2.convertTo(src1, CV_32F); int height = src1.rows; int width = src1.cols; Mat dst = Mat::zeros(src2.size(), src2.type());//创建一副与src1同样的图像，并将像素值全部给0 float alpha = 1.2; float beta = 30; for (int row = 0; row < height; row++) { for (int col = 0; col < width; col++) { if (src1.channels() == 3)//三通道图像 { float b = src1.at<Vec3f>(row, col)[0];//通道1 float g = src1.at<Vec3f>(row, col)[1];//通道2 float r = src1.at<Vec3f>(row, col)[2];//通道3 //修改像素值 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 (src1.channels() == 1)//单通道图像 { float v = src1.at<uchar>(row, col); dst.at<uchar>(row, col) = saturate_cast<uchar>(v*alpha + beta); } } } namedWindow("dst image win", CV_WINDOW_AUTOSIZE); imshow("dst image win", dst); waitKey(0); return 0; }
效果图：
