期刊
COMPUTERS & ELECTRICAL ENGINEERING
卷 70, 期 -, 页码 334-348出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compeleceng.2016.07.010
关键词
Image denoising; SURE-LET; Wiener filter; Thresholding function; Undecimated Haar wavelet transform (UHWT)
类别
资金
- National Natural Science Foundation of China [61401383]
- Qinglan Talent Program of Xianyang Normal University [XSYQL201503]
- Natural Science Foundation of Xianyang Normal University [14XSYK006]
The Stein's unbiased risk estimate and the linear expansion of thresholds (SURE-LET) approach proposed by Luisier et al. is very efficient for image denoising. But the SURE-LET approach adopts the pointwise thresholding function excluding the intrascale information in the wavelet transform, which limits the denoising ability of the technique. In this paper, to improve the SURE-LET approach, a hybrid thresholding function is designed by incorporating the local Wiener filter into the pointwise thresholding function. Experimental results show that the new hybrid thresholding function gets better denoising performance objectively and subjectively compared to the related SURE-LET approaches and the state-of-the-art wavelet-based methods. (C) 2016 Elsevier Ltd. All rights reserved.
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