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Edge Preserving Image De-noising using Adaptive Thresholding

Anjaly Chauhan, Sandhya Tarar


This paper proposes a new image denoising method that is the wavelet threshold denoising of image based on edge detection. Before denoising, wavelet coefficients of an image are first detected, that correspond to edges. Then, the detected coefficients i.e. edges will be preserved from denoising by reducing the threshold coefficient of the original threshold then apply the reduced threshold and this will further protect edges from any damage. In this paper, the theoretical analysis and experimental results are compared to sub-band adaptive thresholding. Then, the efficiency and performance of these denoising methods are compared based on peak signal to noise ratio (PSNR) and visual perception. Combining edge preserving
with image denoising, overcomes the shortcomings of commonly used denoising methods.

Cite this Article
Anjaly Chauhan, Sandhya Tarar. Edge Preserving Image De-noising using
Adaptive Thresholding. Journal of Image Processing & Pattern Recognition Progress. 2015; 2(3): 20–29p.


Image denoising, wavelet edge detection, edge preserving, PSNR, adaptive thresholding

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