Accession Number : ADP007217
Title : Reconstruction of Binary Images,
Corporate Author : CALIFORNIA UNIV BERKELEY DEPT OF STATISTICS
Personal Author(s) : Kooperberg, Charles
Report Date : 1992
Pagination or Media Count : 4
Abstract : We consider the following problem: a black and white image is observed in digitized form. Unfortunately the 'real' image is not observed: at some stage the image has been distorted with noise. Our objective is to remove as much of the noise as possible, to get approximately the original image back. In a more mathematical setting, let x be an m by n array, with entries 0 and 1; x is considered to be a realization of a random variable X. We do not observe the image x. Instead we observe y, a noisy version of x that is a realization of the random variable Y, where the distribution of Y depends on x. We want to estimate x on the basis of y.
Descriptors : *ARRAYS, DISTRIBUTION, ESTIMATES, IMAGES, NOISE, RANDOM VARIABLES, VARIABLES.
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE