SCIENCE CHINA Information Sciences, Volume 61, Issue 4: 049101(2018) https://doi.org/10.1007/s11432-017-9207-9

Nonlocal image denoising using edge-based similarity metric and adaptive parameter selection

More info
  • ReceivedMar 16, 2017
  • AcceptedJul 19, 2017
  • PublishedJan 9, 2018


There is no abstract available for this article.


[1] Tomasi C, Manduchi R. Bilateral filtering for gray and color images. In: Proceedings of the 6th International Conference on Computer Vision. Bombay: IEEE, 1998. 839--846. Google Scholar

[2] Buades A, Coll B, Morel J M. A review of image denoising algorithms, with a new one. Multiscale Model Simul, 2005, 4: 490-530 CrossRef Google Scholar

[3] Tasdizen T. Principal neighborhood dictionaries for nonlocal means image denoising. IEEE Trans Image Process, 2009, 18: 2649-2660 CrossRef PubMed ADS Google Scholar

[4] Chen H H, Ding J J. Nonlocal means image denoising based on bidirectional principal component analysis. In: Proceedings of 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Brisbane: IEEE, 2015. 1265--1269. Google Scholar

[5] Sharifymoghaddam M, Beheshti S, Elahi P. Similarity validation based nonlocal means image denoising. IEEE Signal Process Lett, 2015, 22: 2185-2188 CrossRef ADS Google Scholar

[6] Dabov K, Foi A, Katkovnik V. Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE Trans Image Process, 2007, 16: 2080-2095 CrossRef ADS Google Scholar

[7] Elad M, Aharon M. Image denoising via sparse and redundant representations over learned dictionaries. IEEE Trans Image Process, 2006, 15: 3736-3745 CrossRef ADS Google Scholar

[8] Dong W, Shi G, Li X. Nonlocal image restoration with bilateral variance estimation: a low-rank approach. IEEE Trans Image Process, 2013, 22: 700-711 CrossRef PubMed ADS Google Scholar

Copyright 2020 Science China Press Co., Ltd. 《中国科学》杂志社有限责任公司 版权所有

京ICP备18024590号-1       京公网安备11010102003388号