DocumentCode :
2827344
Title :
Entropy based landcover classification using polarimetric SAR images and GMM method
Author :
Panigrahi, Rajib Kumar ; Mishra, Amit Kumar
Author_Institution :
Department of Electronics and Electrical Engineering, Indian Institute of Technology Guwahati, Guwahati-781039, India
fYear :
2011
fDate :
18-22 Dec. 2011
Firstpage :
1
Lastpage :
4
Abstract :
An unsupervised classification scheme based on the use of polarimetric entropy, alpha angle and complex Wishart classifier is widely used for landcover classification. The segmented zones in the entropy/alpha plane is fed as the initial input to Wishart based classifiers. The Wishart based classifiers highly depend on this initial input. However as the entropy/alpha boundaries are fixed, this scheme does not perform satisfactorily in some cases. We propose a modified version of this scheme in which the entropy/alpha boundaries are set based on the nature of the dataset. The popular Gaussian mixture model clustering method is used in deciding the boundaries. The proposed procedure which is reported in this paper is found to enhance the landcover classification capability and computational efficiency of the classic entropy based Wishart classifiers.
Keywords :
IEEE Xplore; Portable document format; Landcover classification; polarimetric SAR;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applied Electromagnetics Conference (AEMC), 2011 IEEE
Conference_Location :
Kolkata
Print_ISBN :
978-1-4577-1098-8
Type :
conf
DOI :
10.1109/AEMC.2011.6256911
Filename :
6256911
Link To Document :
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