A Comparative Study of Edge Detection in Noisy Images using BM3D Filter

Abstract

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.

Offline signatures matching using haar wavelet subbands

“… Removing the noise Noise reduction is an essential step in image processing due to its importance in obtaining better results, the block matching with three-dimensional filtering (BM3D) denoising is used in this step. Many studies shown that the BM3D filter is very important in term of noise reduction due to its results comparing with other filters [9,10]. The implementation of this filter is explained in detail in [11]  Contrast…”