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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Adaptive edge-preserving image denoising using wavelet transforms

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Author(s):
da Silva, Ricardo Dutra [1] ; Minetto, Rodrigo [1] ; Schwartz, William Robson [1] ; Pedrini, Helio [1]
Total Authors: 4
Affiliation:
[1] Univ Estadual Campinas, Inst Comp, BR-13083852 Campinas, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: PATTERN ANALYSIS AND APPLICATIONS; v. 16, n. 4, p. 567-580, NOV 2013.
Web of Science Citations: 21
Abstract

Image denoising is a relevant issue found in diverse image processing and computer vision problems. It is a challenge to preserve important features, such as edges, corners and other sharp structures, during the denoising process. Wavelet transforms have been widely used for image denoising since they provide a suitable basis for separating noisy signal from the image signal. This paper describes a novel image denoising method based on wavelet transforms to preserve edges. The decomposition is performed by dividing the image into a set of blocks and transforming the data into the wavelet domain. An adaptive thresholding scheme based on edge strength is used to effectively reduce noise while preserving important features of the original image. Experimental results, compared to other approaches, demonstrate that the proposed method is suitable for different classes of images contaminated by Gaussian noise. (AU)

FAPESP's process: 10/10618-3 - Feature Combination for Analysis of Videos Involving Humans
Grantee:William Robson Schwartz
Support Opportunities: Scholarships in Brazil - Post-Doctoral