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Proceedings Paper

Denoising using higher-order statistics
Author(s): Samuel Peter Kozaitis; Sunghee Kim
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Paper Abstract

We used a higher-order correlation-based method for signal denoising. In our approach, we determined which wavelet coefficients contained mostly noise, or signal, based on higher-order statistics. Because the higher that second-order moments of the Gaussian probability function are zero, the third-order correlation coefficient will not have a statistical contribution from Gaussian noise. We obtained results for both 1-D signals and images. In all cases, our approach showed improved results when compared to a more popular denoising method.

Paper Details

Date Published: 1 April 2003
PDF: 8 pages
Proc. SPIE 5102, Independent Component Analyses, Wavelets, and Neural Networks, (1 April 2003); doi: 10.1117/12.485722
Show Author Affiliations
Samuel Peter Kozaitis, Florida Institute of Technology (United States)
Sunghee Kim, Florida Institute of Technology (United States)


Published in SPIE Proceedings Vol. 5102:
Independent Component Analyses, Wavelets, and Neural Networks
Anthony J. Bell; Mladen V. Wickerhauser; Harold H. Szu, Editor(s)

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