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Proceedings Paper

Supervised classification of remotely sensed images using Bayesian network models and Kruskal algorithm
Author(s): Radja Kheddam; Youcef Boudissa; Aichouche Belhadj-Aissa
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Paper Abstract

The aim of this work is to evaluate the performances of three Bayesian networks widely used for supervised image classification. The developed structures are constructed due to Kruskal algorithm which allows the determination of the maximum weight spanning tree by using the mutual information between the attributes. We started by the Bayesian naïve classifier (BNC), which assumes that there is no dependency, between the attributes to classify. In order to relax this strong assumption, we tested the tree augmented naïve Bayes classifier (TANC) where each feature has at most one variable as parent, and the forest augmented naïve Bayes classifier (FANC) where each attribute forms an arbitrary graph rather than just a tree. These classifiers are evaluated using a multispectral image and hyperspectral image in order to analyze the structure classifier complexity according to the number of attributes (04 and 10 spectral bands for the two images respectively). Obtained results are compared with state-of-the art competitor, namely, the SVM classifier. Classified images by TANC and FANC achieved higher accuracies than other classifiers including SVM. It is concluded that the choice of attributes dependencies significantly contributes to the discrimination of subjects on the ground. Thus, Bayesian networks appear as powerful tool for multispectral and hyperspectral image classification.

Paper Details

Date Published: 10 October 2017
PDF: 12 pages
Proc. SPIE 10427, Image and Signal Processing for Remote Sensing XXIII, 104271K (10 October 2017); doi: 10.1117/12.2278122
Show Author Affiliations
Radja Kheddam, Univ. des Sciences et de la Technologie Houari Boumediene (Algeria)
Youcef Boudissa, Univ. des Sciences et de la Technologie Houari Boumediene (Algeria)
Aichouche Belhadj-Aissa, Univ. des Sciences et de la Technologie Houari Boumediene (Algeria)


Published in SPIE Proceedings Vol. 10427:
Image and Signal Processing for Remote Sensing XXIII
Lorenzo Bruzzone, Editor(s)

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