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Proceedings Paper

Reduction of multiplicative noise using higher-order statistics
Author(s): Samuel Peter Kozaitis; Anurat Ingun; Rufus H. Cofer
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Paper Abstract

We used a higher-order correlation-based method for signal denoising of images corrupted by multiplicative noise. Using the logarithm of an image, we applied a third-order correlation technique for identification of wavelet coefficients that contained mostly signal. In our approach, we examined wavelet coefficients in an environment where the contribution from the second-order moment of the noise had been reduced. Our results compared favorably and were less sensitive to threshold selection when compared to a second-order wavelet denoising method.

Paper Details

Date Published: 12 September 2003
PDF: 7 pages
Proc. SPIE 5095, Algorithms for Synthetic Aperture Radar Imagery X, (12 September 2003); doi: 10.1117/12.487754
Show Author Affiliations
Samuel Peter Kozaitis, Florida Institute of Technology (United States)
Anurat Ingun, Florida Institute of Technology (United States)
Rufus H. Cofer, Florida Institute of Technology (United States)


Published in SPIE Proceedings Vol. 5095:
Algorithms for Synthetic Aperture Radar Imagery X
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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