Image denoising based on Gaussian and non-Gaussian assumption
type: Item
instance of: scholarly article
zbMATH Open document ID: 1252.94028
DOI: 10.1142/S0219691312500142
author: Ping Zhao
author: Zhaowei Shang
author: Chun Zhao
published in: International Journal of Wavelets, Multiresolution and Information Processing
publication date: 2012-09-03T00:00:00Z
Mathematics Subject Classification ID: 94A08
Mathematics Subject Classification ID: 65T60
zbMATH DE Number: 6075905
zbMATH Keywords: complex dual-tree discrete wavelet transform
zbMATH Keywords: image denoising
describes a project that uses: DT-CWT
MaRDI profile type: Publication
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title: Image denoising based on Gaussian and non-Gaussian assumption
review text: The authors present here an adaptive intra-scale noise removal scheme and estimate clean wavelet coefficients using new prior information with Bayesian estimation technique. The effectiveness of the algorithm proposed is compared with others. It is observed that the Gaussian assumption is very effective for the orthogonal wavelet transform and the non-Gaussian bivariate distribution (cf. [\textit{L. Sendur} et al., IEEE Signal Process. Lett. 9, 438--441 (2002)]) is very effective for complex wavelet coefficients.
reviewed by: H. P. Dikshit
description: scientific article; zbMATH DE number 6075905