Values for the Fuzzy -means Classifier in Change Detection for Remote Sensing
نویسندگان
چکیده
We discuss an approach to change detection in digital remotely sensed imagery that relies on the Fuzzy Post Classification Comparison technique. We use the fuzzy -means classifier together with the Mahalanobis distance as the basis for a metric of class membership for a individual pixel. We note that the value of the fuzzy exponent in a fuzzy classifier is based on the ratios of the reciprocals of the class Mahalanobis Distances. The paper is an empirical investigation of this value and concludes with recommendations for the value of the fuzzy exponent .
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تاریخ انتشار 2001