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A new scale adaptive wavelet thresholding method for denoising using chi-square test statistic

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Title A new scale adaptive wavelet thresholding method for denoising using chi-square test statistic
 
Creator DAS, A
DESAI, UB
VAIDYA, PP
 
Subject gaussian noise
adaptive signal processing
interference suppression
signal denoising
statistical analysis
wavelet transforms
 
Description In this paper we develop a new scale adaptive scheme of wavelet thresholding for noise removal. The method uses chi-square test statistics (CTS) to discriminate between noise and signal among the wavelet coefficients. The scheme uses CTS as a ruler to measure the similarity between the statistical model and the true distribution of noise. The basic philosophy of the proposed method is similar to a recursive hypothesis testing procedure. We demonstrate this method by denoising signals corrupted with additive zero-mean Gaussian noise.
 
Publisher IEEE
 
Date 2008-12-23T06:48:39Z
2011-11-28T03:57:37Z
2011-12-15T09:56:22Z
2008-12-23T06:48:39Z
2011-11-28T03:57:37Z
2011-12-15T09:56:22Z
2002
 
Type Article
 
Identifier Proceedings of the 9th International Conference on Electronics, Circuits and Systems (V 3), Dubrovnik, Croatia, 15-18 September 2002, 859-862
0-7803-7596-3
10.1109/ICECS.2002.1046383
http://hdl.handle.net/10054/483
http://dspace.library.iitb.ac.in/xmlui/handle/10054/483
 
Language en