Estimation of shape parameter for generalized Gaussian distributions in subband decompositions of video

Abstract

A subband decomposition scheme for video signals, in which the original or difference frames are each decomposed into 16 equal-size frequency subbands, is considered. Westerink et al. (1991) have shown that the distribution of the sample values in each subband can be modeled with a probability density function (PDF) where three parameters, mean, variance, and shape are required to uniquely determine the PDF. To estimate the shape parameter, a series of statistical goodness-of-fit tests such as Kolmogorov-Smirnov or chi-squared tests have been used. A simple alternative method to estimate the shape parameter for the generalized Gaussian PDF is proposed that significantly reduces the number of computations by eliminating the need for any statistical goodness-of-fit test. >