Proceedings of SPIE - the International Society for Optical Engineering
We showed that a hard threshold for wavelet denoising based on higher order statistics is comparable to a second order soft threshold. The hard threshold can be made adaptive by using a third order statistic as an estimate of the noise. In addition, the relationship between an adaptive hard threshold and retaining a fraction of wavelet coefficients is shown. Qualitative and quantitative metrics based on the mean-squared error are used to compare the hard thresholding and a soft-thresholding technique, BayesShrink.
Kozaitis, S. P., & Young, T. (2009). Denoising using adaptive thresholding and higher order statistics. Paper presented at the Proceedings of SPIE - the International Society for Optical Engineering, , 7343 doi:10.1117/12.818719