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06_Opencv图像混合
一.图像的线性混合
dst = alpha*src1 + beta*src2
- beta = 1-alpha
- alpha的取值为:0.01.0之间,同理,beta取值也在0.01.0之间
- gama不取零的情况:
dst = alpha*src1 + beta*src2 + gama
二.Opencv中图像线性混合的API
addWeighted(const CvArr *src1, double alpha, const CvArr *src2, double beta, double gamma, CvArr *dst)
- 第一个参数为输入的源图像src1, 第二个参数为输入图像src1的系数值, 第三个参数为输入的源图像src2, 第四个参数为输入图像src2的系数值, 第五个参数为gama值, 第六个参数为混合后的结果
- 只有图像src1与src2的大小和类型一样时,才能进行混合
三.使用读取像素的方式实现混合
Mat src1 = imread("/Users/zhixingao/Downloads/android/OpencvForCPlus/素材/图像混合2.jpg");
if(!src1.data) {
printf("could not load image src1...\n");
return -1;
}
Mat src2 = imread("/Users/zhixingao/Downloads/android/OpencvForCPlus/素材/图像混合1.jpg");
if(!src2.data) {
printf("could not load image src2...\n");
return -1;
}
namedWindow("input image1", CV_WINDOW_AUTOSIZE);
imshow("input image1", src1);
namedWindow("input image2", CV_WINDOW_AUTOSIZE);
imshow("input image2", src2);
if(src1.cols == src2.cols && src1.rows == src2.rows && src1.type() == src2.type()) {
//通过读写像素值的方式实现图像混合
float alpha = 0.5;
Mat dst(src1.size(), src1.type());
int cols = src1.cols;
int rows = src1.rows;
int channels = src1.channels();
for(int row=0; row<rows; row++) {
for(int col=0; col<cols; col++) {
if(channels == 3) {
Vec3b src1Intensity = src1.at<Vec3b>(row, col);
Vec3b src2Intensity = src2.at<Vec3b>(row, col);
uchar src1B = src1Intensity[0];
uchar src1G = src1Intensity[1];
uchar src1R = src1Intensity[2];
uchar src2B = src2Intensity[0];
uchar src2G = src2Intensity[1];
uchar src2R = src2Intensity[2];
dst.at<Vec3b>(row, col)[0] = saturate_cast<uchar>(alpha * src1B + (1-alpha) * src2B);
dst.at<Vec3b>(row, col)[1] = saturate_cast<uchar>(alpha * src1G + (1-alpha) * src2G);
dst.at<Vec3b>(row, col)[2] = saturate_cast<uchar>(alpha * src1R + (1-alpha) * src2R);
} else {
uchar src1Intensity = src1.at<uchar>(row, col);
uchar src2Intensity = src2.at<uchar>(row, col);
dst.at<uchar>(row, col) = saturate_cast<uchar>(alpha * src1Intensity + (1-alpha) * src2Intensity);
}
}
}
namedWindow("output image", CV_WINDOW_AUTOSIZE);
imshow("output image", dst);
} else {
printf("can not blend src1 and src2 beacause of size and type is not same...\n");
return -1;
}
四.使用cv::addWeighted实现图像混合
Mat src1 = imread("/Users/zhixingao/Downloads/android/OpencvForCPlus/素材/图像混合2.jpg");
if(!src1.data) {
printf("could not load image src1...\n");
return -1;
}
Mat src2 = imread("/Users/zhixingao/Downloads/android/OpencvForCPlus/素材/图像混合1.jpg");
if(!src2.data) {
printf("could not load image src2...\n");
return -1;
}
namedWindow("input image1", CV_WINDOW_AUTOSIZE);
imshow("input image1", src1);
namedWindow("input image2", CV_WINDOW_AUTOSIZE);
imshow("input image2", src2);
if(src1.cols == src2.cols && src1.rows == src2.rows && src1.type() == src2.type()) {
float alpha = 0.5;
Mat dst(src1.size(), src1.type());
//通过addWeighted方式实现图像混合
addWeighted(src1, alpha, src2, 1.0-alpha, 0.0, dst);
namedWindow("output image", CV_WINDOW_AUTOSIZE);
imshow("output image", dst);
} else {
printf("can not blend src1 and src2 beacause of size and type is not same...\n");
return -1;
}