Research and Optimization on BM3D Denoising Algorithm-Reference-Cited by-同舟云学术

Research and Optimization on BM3D Denoising Algorithm

Published:2014-09 Issue: Volume:644-650 Page:3976-3979
ISSN:1662-7482
Container-title:Applied Mechanics and Materials
language:
Short-container-title:AMM

Author:

Guo Zi Yu¹,Zhou Xiao Bo¹

Affiliation:

1. Beijing Jiao Tong University

Abstract

By grouping up the similar blocks in the picture and Collaborative Filtering, BM3D gets a good denoising effect. But denoising performance declined when the noise enhanced. A reason of poor denoising effect in strong noise was put forward in this paper. Then the denoising ability of BM3D was enhanced by optimizing the parameters.BM3D is proved superior to the traditional filtering denoising algorithm and the optimized BM3D gets a better effect than the original one in strong noise in simulation.

Publisher

Trans Tech Publications, Ltd.

Link

https://www.scientific.net/AMM.644-650.3976.pdf

Reference5 articles.

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3. Dabov K, Foi A, Katkovnik V, et al. BM3D image denoising with shape-adaptive principal component analysis. Proceedings of Workshop on Signal Processing with Adaptive Sparse Structured Representations, 2009, 221-226.

4. Xiangle Liu, Xiangchu Feng. Image denoising by mixing wavelet transformation with sparse 3D collaborative filtering[J]. COMPUTER ENGINEERING AND APPLICATIONS, 2010, 46(16): 185-187.

5. Yingkun Hou. Research on Nonlocal Transform Domain Image Denoising and Enhancement and Their Performance Evaluation[D], Nanjin: Nanjin University of Science and Technology, (2012).

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