Similarity measure between vector data bases and optical images for change detection

This paper addresses the problem of defining a similarity measure between an observed Gaussian image and a binary image constructed from a cartographic database. The main idea is to assume that the binary image has been obtained by thresholding an unobserved Gaussian image correlated with the observed image. The proposed statistical model is then used to estimate its unknown parameters using the maximum likelihood method. The paper discusses a possible application to change detection between a cartographic vector data base and an optical image.