Image Denoising via Residual Kurtosis Minimization
Tristan A. Hearn, Lothar Reichel · Numerical Mathematics Theory Methods and Applications · 2015
A new algorithm for the removal of additive uncorrelated Gaussian noise from a digital image is presented. The algorithm is based on a data driven methodology for the adaptive thresholding of wavelet coefficients. This methodology is derived from higher order statistics of the residual image, and requires no a priori estimate of the level of noise contamination of an image.