Modelling Image Redundancy
Abstract
C.E. Shannon in his Information Theory defined a rate of information transmission of a transmitter-receiver couple. We use this concept to define three models of image redundancy. First we apply information theory to a simple model considering an image as a set of isolated pixels. Then we introduce a Markov Random Field model to take into account the neighbourhood of a pixel. We show that we have to determine some parameters of the MRF in order to obtain sufficient statistics from common satellite images, and we propose a measure based on a generalized Ising model. Our third model considers the correspondence between grey level vectors of cliques. We introduce a distance in the grey level space to solve the problem of insufficient statistics. Finally, results for the proposed definitions are presented for some synthetic and a large variety of SPOT XS1, XS2 and XS3 image triples and are compared to the classical correlation coefficient measure.