Proceedings of SPIE - the International Society for Optical Engineering
We reduced noise in images using a higher-order, correlation-based method. In this approach, wavelet coefficients were classified as either mostly noise or mostly signal based on third-order statistics. Because the higher than second-order moments of the Gaussian probability function are zero, the third-order correlation coefficient may not have a statistical contribution from Gaussian noise. Using a detection algorithm derived from third-order statistics, we determined if a wavelet coefficient was noisy by looking at its third-order correlation coefficient. Using imagery of space shuttle tiles, our results showed that the minimum mean-squared error obtained using third-order statistics was often less than that using second-order statistics.
Kozaitis, S. P. (2006). Denoising of imagery for inspection tasks using higher-order statistics. Paper presented at the Proceedings of SPIE - the International Society for Optical Engineering, 6383 doi:10.1117/12.686619