Fuzzy Logic Based Satellite Image Classification: Generation of Fuzzy Membership Function and Rule from Training Set
نویسندگان
چکیده
The paper presents an automated method for generating fuzzy rules and fuzzy membership functions for pattern classification from training sets of examples. Initially, fuzzy subspaces are created from the partitions formed by the minimum and maximum of individual feature values of each class. The initial membership functions are determined according to the generated fuzzy partitions. The fuzzy subspaces are further iteratively partitioned if the user-specified classification performance has not been archived on the training set. Our classifier was trained and tested on patterns consisting of the DN of each band, (SS1, SS2. SS3), extracted from SPOT multispectral scene. The result represents that our method has higher generalization power.
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