A Novel Theoretical Framework for Unsupervised Change Detection Based on CVA in Polar Domain

In this paper a framework for a formal definition and a theoretical study of the change vector analysis (CVA) technique is proposed. This framework, which is based on the representation of the CVA in polar coordinates, aims at: (i) introducing formal definitions in the polar domain for a better general description and understanding of the information present in spectral change vectors; (ii) analyzing from a theoretical point of view the distributions of changed and unchanged pixels in the polar domain; (iii) driving the implementation of proper preprocessing procedures for multitemporal images on the basis of the results of the theoretical study on the distributions; and (iv) defining a solid background for the development of advanced and accurate automatic change-detection algorithms in the polar domain. The findings derived from the theoretical analysis on the statistical models of classes have been validated on real multispectral and multitemporal remote sensing images.