A survey of edge-preserving image denoising methods

Paras Jain () and Vipin Tyagi ()
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Paras Jain: Jaypee University of Engineering & Technology
Vipin Tyagi: Jaypee University of Engineering & Technology

Information Systems Frontiers, 2016, vol. 18, issue 1, No 10, 159-170

Abstract: Abstract Reducing noise has always been one of the standard problems of the image analysis and processing community. Often though, at the same time as reducing the noise in a signal, it is important to preserve the edges. Edges are of critical importance to the visual appearance of images. So, it is desirable to preserve important features, such as edges, corners and other sharp structures, during the denoising process. This paper presents a review of some significant work in the area of image denoising. It provides a brief general classification of image denoising methods. The main aim of this survey is to provide evolution of research in the direction of edge-preserving image denoising. It characterizes some of the well known edge-preserving denoising methods, elaborating each of them, and discusses the advantages and drawbacks of each. Basic ideas and improvement of the denoising methods are also comprehensively summarized and analyzed in depth. Often, researchers face difficulty in selecting an appropriate denoising method that is specific to their purpose. We have classified and systemized these denoising methods. The key goal of this paper is to provide researchers with background on a progress of denoising methods so as to make it easier for researchers to choose the method best suited to their aims.

Keywords: Bilateral filtering; Edge-preserving filtering; Stein’s unbiased risk estimate (SURE) minimization; Wavelet transform; Wavelet thresholding (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10796-014-9527-0

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