Optimal processing techniques for SAR

In the history of SAR image processing, many algorithms have been proposed to tackle the problems of segmentation, classification and edge detection. They are typically heuristic in basis, and more successful on some types of imagery than others. With the development of global optimization methods it has now become possible to produce optimal techniques; that is, those which can genuinely achieve the optimal solution of the posed problem. The problem is characterized by an objective function and the chosen optimization technique. The most successful and wide-spread method has been simulated annealing and we detail its application in the fields of segmentation and classification. In particular, we detail how to optimally quantify the relationship between competing terms within the objective function. The performance of the resulting algorithm on various SAR imagery is given.