Edge detection in noisy images is a bargain between denoising and edge preserving capability. Hence, various smoothing filters are studied in the viewpoint of edge detection too. In this paper, a method for edge detection in noisy images has been discussed which uses BM3D (Block Matching 3D) filter for image denoising. A grayscale noisy image is denoised using Gaussian, Bilateral, Median and BM3D filters for comparison. Then the edge map of the image is obtained by applying edge detection operators like Sobel, Prewitt, Roberts and Canny's and the results are analyzed in all these cases. Further, the noise level is increased and the behavior of BM3D filter is studied in the viewpoint of edge preservability. Results show that the method with BM3D filter performs better than the other methods in comparison for edge detection. The results are quantitatively verified using Pratt's figure of merit and Performance Ratio.
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