Ho, Yuk-Fan and Ling, Wing-Kuen and Tam, Kwong-Shun (2003) Denoising by multiwavelet singularity detection. In: International Conference on Neural Networks and Signal Processing, December 2003, Nanjing.

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Abstract

Wavelet denoising by singularity detection was proposed as an algorithm that combines Mallat and Donoho’s denoising approaches. With wavelet transform modulus sum, we can avoid the error and ambiguities of tracing the modulus maxima across scales and the complicated and computationally demanding reconstruction process. We can also avoid the visual artifacts produced by shrinkage. In this paper, we investigate a multiwavelet denoising algorithm based on a modified singularity detection approach. Improved signal denoising results are obtained in comparison to the single wavelet case.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Wavelet denoising by singularity detection was proposed as an algorithm that combines Mallat and Donoho’s denoising approaches. With wavelet transform modulus sum, we can avoid the error and ambiguities of tracing the modulus maxima across scales and the complicated and computationally demanding reconstruction process. We can also avoid the visual artifacts produced by shrinkage. In this paper, we investigate a multiwavelet denoising algorithm based on a modified singularity detection approach. Improved signal denoising results are obtained in comparison to the single wavelet case.
Keywords:	multiwavelet denoising, singularity detection
Subjects:	H Engineering > H610 Electronic Engineering
Divisions:	College of Sciences > Faculty of Science > Lincoln School of Engineering
Depositing User:	Wing-Kuen Ling
Date Deposited:	06 Aug 2010 09:19
Last Modified:	13 Mar 2013 08:44
URI:	http://eprints.lincoln.ac.uk/id/eprint/3127

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