TY - JOUR
T1 - Image Denoising via Residual Kurtosis Minimization
JO - Numerical Mathematics: Theory, Methods and Applications
VL - 3
SP - 406
EP - 424
PY - 2015
DA - 2015/08
SN - 8
DO - http://doi.org/10.4208/nmtma.2015.m1337
UR - https://global-sci.org/intro/article_detail/nmtma/12416.html
KW - 
AB - <p style="text-align: justify;">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.</p>