STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Image Processing & Pattern Recognition Progress

Edge Preserving Image De-noising using Adaptive Thresholding

  1. Anjaly Chauhan
  2. Sandhya Tarar

Abstract

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 preservingwith image denoising, overcomes the shortcomings of commonly used denoising methods.Cite this ArticleAnjaly Chauhan, Sandhya Tarar. Edge Preserving Image De-noising usingAdaptive Thresholding. Journal of Image Processing & Pattern Recognition Progress. 2015; 2(3): 20–29p.

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