Design of fuzzy supervised classification system for single-channel SAR images

A fuzzy supervised classification system for single-channel SAR images is designed. The system mainly consists of two parts: a fuzzy supervised partitioner and a fuzzy vector quantizer both of which employ fuzzy theory. The fuzzy partitioner is the key part that determines the classification accuracy level and the fuzzy vector quantizer is appended to improve the accuracy. The use of the system includes system training, data fuzzy analysis, result display and classification accuracy estimation. The classification result is compared with GML classification result to evaluate the system's performance.