Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. Supervised classification of remotely sensed data requires systematic collection of training samples for classes of interest. Image visual interpretation is important in training...

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Bibliographic Details
Main Author:	Teoh, Chin Chuang
Format:	Thesis
Language:	English English
Published:	2005
Subjects:	Data compression - Remote sensing - Case studies
Online Access:	http://psasir.upm.edu.my/id/eprint/6062/ http://psasir.upm.edu.my/id/eprint/6062/1/FK_2005_49.pdf

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