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A SURE Based Sub-band Adaptive De-noising Method
Gong TR(宫铁瑞); Yang ZJ(杨志家); Wang GS(王庚善); Jiao P(焦平)
Department工业控制网络与系统研究室
Conference Name2016 2nd IEEE International Conference on Computer and Communications (ICCC 2016)
Conference DateOctober 14-17, 2016
Conference PlaceChengdu, China
Source Publication2016 2nd IEEE International Conference on Computer and Communications (ICCC 2016)
PublisherIEEE
Publication PlaceNew York
2016
Pages2637-2640
Indexed ByEI ; CPCI(ISTP)
EI Accession number20172303742579
WOS IDWOS:000411576804061
Contribution Rank1
ISSN1095-2055
ISBN978-1-4673-9026-2
KeywordWavelet Denoising Sub-band Adaptive Denoising Stein’s Unbiased Risk Estimate (Sure) Minimization
AbstractThis paper introduces a different approach to wavelet denoising. Unlike traditional soft or hard thresholding based wavelet domain schemes, we employ an odd-term reserving polynomial function with flexible coefficients as the noisy signal estimator. Meanwhile we adopt Stein’s Unbiased Risk Estimate (SURE) to give an unbiased estimate of the mean-squared error (MSE) between clean and denoised signal. The polynomial function coefficients are determined by minimizing the Stein’s unbiased risk estimate. This SURE based property makes our approach only depend on the noisy signal, not on the clean one. Furthermore, the polynomial function structure makes coefficients solving a linear minimization problem, which is more efficient and easy to solve comparing with gradient based minimization problem. We test the proposed approach on a set of signals and the simulation results show our approach performs better than those soft and hard thresholding based methods (e.g. Sure Shrink, MiniMaxShrink and VisuShrink) in both MSE and signal-to-noise ratio (SNR) sense.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/19506
Collection工业控制网络与系统研究室
Corresponding AuthorGong TR(宫铁瑞)
Affiliation1.Department of Industrial Control Networks and Systems, Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, China
2.University of Chinese Academy of Sciences, Beijing, China
Recommended Citation
GB/T 7714
Gong TR,Yang ZJ,Wang GS,et al. A SURE Based Sub-band Adaptive De-noising Method[C]. New York:IEEE,2016:2637-2640.
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