Optimal approach to SAR image segmentation and classification

Many algorithms have been proposed for the segmentation and classification of SAR imagery. Typically these are heuristic in basis, and more successful on some types of imagery than others. Methods based on global optimisation techniques can achieve the optimal solution of the posed problem; the algo rithm is then characterised by an objective function and the chosen optimis ation technique. The authors construct an appropriate objective function fo r SAR segmentation or classification, and show how to optimally quantify th e relationship between the competing terms within it. This removes the prev ious need for the introduction of heuristics. Also described is an implemen tation based on simulated annealing, in which considerable attention has be en paid to details, and examples are given of the resulting algorithm's per formance upon real data.