Reduction of multiplicative noise using higher-order statistics
Samuel P. Kozaitis, Anurat Ingun, Rufus H. Cofer · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
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.