DocumentCode :
249641
Title :
Local histogram based classification of SAR images using spatially dependent mixtures
Author :
Kayabol, K.
Author_Institution :
Gebze Inst. of Technol., Gebze, Turkey
fYear :
2014
fDate :
27-30 Oct. 2014
Firstpage :
5157
Lastpage :
5161
Abstract :
We propose a local histogram based mixture model for synthetic aperture radar image classification. In this model, local histograms are modeled by multinomial densities. The model has also a spatially dependent class label prior to achieve a smooth contextual classification. Based on the classification results obtained on real TerraSAR-X image, it is shown that the proposed model is capable of more accurately classifying pixels especially in the heterogeneous regions, like urban areas, compared to conventional mixture model.
Keywords :
image classification; mixture models; radar imaging; synthetic aperture radar; SAR image pixel classification; TerraSAR-X image; local histogram based mixture model; multinomial density; smooth contextual classification; spatially dependent mixture model; synthetic aperture radar; Bayes methods; Computational modeling; Context modeling; Histograms; Niobium; Smoothing methods; Synthetic aperture radar; SAR images; contextual image classification; local histograms; mixture models; multinomial logistic regression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/ICIP.2014.7026044
Filename :
7026044
Link To Document :
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