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المؤلفMelgani, Farid
المؤلفAl-Hashemy, Bakir A. R.
المؤلفTaha, Saleem M. R.
تاريخ الإتاحة2009-11-25T13:06:36Z
تاريخ النشر2001
اسم المنشورEngineering Journal of Qatar University
الاقتباسEngineering Journal of Qatar University, 2001, Vol. 14, Pages 77-104.
معرّف المصادر الموحدhttp://hdl.handle.net/10576/7990
الملخصFuzzy Classification is 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 ofLandsat TM data show the promising performance of the method and, particularly, the classification time. These results are compared with those produced by the Maximum Likelihood method and a non-parametric method based on the use of Artificial Neural Networks.
اللغةen
الناشرQatar University
الموضوعEngineering: Research Papers
العنوانAn Evaluation Of The Explicit Fuzzy Method Using Parametric And Non-Parametric Approaches For Supervised Classification Of Multispectral Remote Sensing Data
النوعArticle
الصفحات77-104
رقم المجلد14
dc.accessType Open Access


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