opencv 图像去脏点
时间: 2023-08-20 21:06:37 浏览: 70
要使用OpenCV进行图像去脏点,可以使用中值滤波或FastNlMeansDenoisingColored方法。中值滤波可以通过对每个通道进行中值滤波来去除噪点。代码示例如下:
```cpp
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>
using namespace std;
using namespace cv;
int main() {
Mat srcImage = imread("input.jpg");
if (!srcImage.data){
cout << "Failed to read image" << endl;
return -1;
}
Mat srcGray;
cvtColor(srcImage, srcGray, CV_BGR2GRAY);
// 中值滤波去噪点
medianBlur(srcGray, srcGray, 1.5);
// 二值化提取修复区域
Mat srcThres;
threshold(srcGray, srcThres, 242, 255, CV_THRESH_BINARY);
// 修复图像
Mat inpaint_result;
inpaint(srcImage, srcThres, inpaint_result, 1, INPAINT_TELEA);
imshow("Original Image", srcImage);
imshow("Inpaint Result", inpaint_result);
waitKey(0);
return 0;
}
```
另一种方法是使用FastNlMeansDenoisingColored方法,它可以去除彩色图像中的噪点。代码示例如下:
```cpp
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>
using namespace std;
using namespace cv;
int main() {
Mat srcImage = imread("input.jpg");
if (!srcImage.data){
cout << "Failed to read image" << endl;
return -1;
}
Mat result;
fastNlMeansDenoisingColored(srcImage, result);
imshow("Original Image", srcImage);
imshow("Denoised Image", result);
waitKey(0);
return 0;
}
```
请注意,以上代码中的"input.jpg"应替换为您要处理的图像的路径。
#### 引用[.reference_title]
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