Ho, Yuk-Fan, 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.
Full content URL: http://dx.doi.org/10.1109/ICNNSP.2003.1279349
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Item Type: | Conference or Workshop contribution (Paper) |
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Item Status: | Live Archive |
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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.
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. |
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Keywords: | multiwavelet denoising, singularity detection |
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Subjects: | H Engineering > H610 Electronic Engineering |
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Divisions: | College of Science > School of Engineering |
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ID Code: | 3127 |
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Deposited On: | 06 Aug 2010 09:19 |
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