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Title: A new scale adaptive wavelet thresholding method for denoising using chi-square test statistic
Authors: DAS, A
Keywords: Gaussian Noise
Adaptive Signal Processing
Interference Suppression
Signal Denoising
Statistical Analysis
Wavelet Transforms
Issue Date: 2002
Publisher: IEEE
Citation: Proceedings of the 9th International Conference on Electronics, Circuits and Systems (V 3), Dubrovnik, Croatia, 15-18 September 2002, 859-862
Abstract: 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.
URI: 10.1109/ICECS.2002.1046383
ISBN: 0-7803-7596-3
Appears in Collections:Proceedings papers

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