Reduction of multiplicative noise using higher-order statistics

Samuel Peter Kozaitis; Anurat Ingun; Rufus H. Cofer

doi:10.1117/12.487754

12 September 2003 Reduction of multiplicative noise using higher-order statistics

Samuel Peter Kozaitis; Anurat Ingun; Rufus H. Cofer

Author Affiliations +

Proceedings Volume 5095, Algorithms for Synthetic Aperture Radar Imagery X; (2003) https://doi.org/10.1117/12.487754
Event: AeroSense 2003, 2003, Orlando, Florida, United States

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.

Citation Download Citation

Samuel Peter Kozaitis, Samuel Peter Kozaitis, Anurat Ingun, Anurat Ingun, Rufus H. Cofer, Rufus H. Cofer, } "Reduction of multiplicative noise using higher-order statistics", Proc. SPIE 5095, Algorithms for Synthetic Aperture Radar Imagery X, (12 September 2003); doi: 10.1117/12.487754; https://doi.org/10.1117/12.487754

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