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OpenCV Filters - bilateralFilter

Applies the bilateral filter to an image.

C++: void blur(InputArray src, OutputArray dst, Size ksize, Point anchor=Point(-1,-1), int borderType=BORDER_DEFAULT ) 

Python: cv2.blur(src, ksize[, dst[, anchor[, borderType]]]) → dst 


Parameters:
  • src – Source 8-bit or floating-point, 1-channel or 3-channel image.
  • dst – Destination image of the same size and type as src .
  • d – Diameter of each pixel neighborhood that is used during filtering. If it is non-positive, it is computed from sigmaSpace .
  • sigmaColor – Filter sigma in the color space. A larger value of the parameter means that farther colors within the pixel neighborhood (see sigmaSpace ) will be mixed together, resulting in larger areas of semi-equal color.
  • sigmaSpace – Filter sigma in the coordinate space. A larger value of the parameter means that farther pixels will influence each other as long as their colors are close enough (see sigmaColor ). When d>0 , it specifies the neighborhood size regardless of sigmaSpace . Otherwise, d is proportional to sigmaSpace .

The function applies bilateral filtering to the input image, as described in http://www.dai.ed.ac.uk/CVonline/LOCAL_COPIES/MANDUCHI1/Bilateral_Filtering.html bilateralFilter can reduce unwanted noise very well while keeping edges fairly sharp. However, it is very slow compared to most filters.

Sigma values: For simplicity, you can set the 2 sigma values to be the same. If they are small (< 10), the filter will not have much effect, whereas if they are large (> 150), they will have a very strong effect, making the image look “cartoonish”.

Filter size: Large filters (d > 5) are very slow, so it is recommended to use d=5 for real-time applications, and perhaps d=9 for offline applications that need heavy noise filtering.

This filter does not work inplace.

Reference: OpenCV Documentation -  bilateralFilter

Example
This is a sample code (C++) with images for opencv bilateral filter filter.

 string imgFileName = "lena.jpg";

 cv::Mat src = cv::imread(imgFileName);
 if (!src.data){
    cout << "Unable to open file" << endl;
    getchar();
    return 1;
 }

 cv::Mat dst;
 cv::bilateralFilter(src, dst, 20, 100, 100);

 cv::namedWindow("Source");
 cv::namedWindow("Filtered");

 cv::imshow("Source", src);
 cv::imshow("Filtered", dst);
 cv::waitKey(0);

 cv::imwrite("BilateralFilter.jpg", dst);

 return 0;

Filtered Image Source Image




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