A hybrid edge-preserving image smoothing scheme for noise removal

A hybrid edge-preserving image smoothing scheme for noise removal
Title:
A hybrid edge-preserving image smoothing scheme for noise removal
Other Titles:
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publication Date:
19 April 2015
Citation:
J. Zheng and Z. Li, "A hybrid edge-preserving image smoothing scheme for noise removal," 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), South Brisbane, QLD, 2015, pp. 1270-1274. doi: 10.1109/ICASSP.2015.7178174
Abstract:
In this paper, we propose a new image denoising scheme that is an integration of a content-adaptive guided filter and a collaborative Wiener filter. The proposed scheme consists of two steps. First a content-adaptive guided filter, which smoothes image based on spatial similarity within a local window, is applied. The content adaptive guided filter can efficiently preserve edges while smoothing noise. A preliminary estimation of noise-free image can be obtained by the content-adaptive guided filter. In the second step, a patch-grouping based collaborativeWiener filter is adopted to exploit non-local similarity, and outputs final denoised image. Compared to the state-of-the-art denoising scheme, BM3D, the proposed method is more efficient in computation. Moreover, simulation results have shown that the proposed method can achieve comparable PSNR values and better visual quality on denoising of textural images.
License type:
PublisherCopyrights
Funding Info:
Description:
(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISSN:
1520-6149
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