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An explicit fuzzy supervised classification method for multispectral remote sensing images
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AI
DOI：10.1109/36.823921.png)
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Fuzz classification has become of great interest because, of its capacity to provide more useful information for geographic information systems. This paper describes an explicit fuzzy supervised classification method which consists of three steps. The explicit fuzzyfication is the first step where the pixel is transformed into a matrix of membership degrees representing the fuzzy inputs-of the process. Then, in the second step, a MIN fuzzy reasoning rule followed by a rescaling operation are applied,to deduce the fuzzy outputs, or in other words, the fuzzy classification of the pixel. Finally, a defuzzyfication step is carried out to produce a hard classification. The classification results on Landsat TM data demonstrate the promising performances of the method and comparatively short classification time.
Keyword:
fuzzy classification
fuzzyfication
fuzzy reasoning rule
remote sensing
期刊
IF:
8.6
论文数:
2.1W
被引数:
10.7W
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