Context classification using evidential relaxation

A relaxation scheme is proposed in which Dempster-Shafer evidential theory is used to bring the effect of the spatial neighbourhood of a pixel into a classification. The benefits include the ability to incorporate uncertainty, both in the central pixel´s labels and in those of its neighbours. A stopping criterion can be devised by increasing the uncertainty contribution of the neighbourhood to unity within a prescribed number of iterations. The number of iterations to be used is governed by several factors, including an estimate of how far out in the neighbourhood pixels are assumed to be influential. As with standard relaxation labelling, but unlike many other context sensitive methods, the evidential approach can be initialised from the results of a separate point statistical classification of the image. Results with model and real data are demonstrated