1. An image processing method comprising the steps of: a. scanning an image to produce an image signal; b. digitizing the image signal to produce a digital image having pixel amplitude values; c. forming an image difference signal by taking differences between successive pixel amplitude values in the digital image; d. segmenting in segmenting means the digital image into segments of pixel amplitude values having constant variance by applying a generalized likelihood ratio test (GLRT) to the image difference signal, to identify image segments, the GLRT testing for the hypothesis H.sub..phi. that a first set of image amplitude difference values from a Laplacian distribution having a variance .sigma. are statistically similar to a second set of image amplitude difference values having a variance .sigma..sub.0 to within a confidence level .alpha., where .alpha. is an operator input value, the GLRT employing a generalized likelihood ratio (GLR) that is the ratio of maximum likelihood (ML) estimators for the variance .sigma. of a distribution having a Laplacian probability density function (pdf); e. supplying said segments to image processing means; f. processing in said image processing means the digital image employing said identified image segments to produce a processed digital image; and g. supplying said processed digital image to an output device.