DocumentCode :
1315999
Title :
PSO-based automatic relevance determination and feature selection system for hyperspectral image classification
Author :
Xiangrong Zhang ; Wenna Wang ; Yangyang Li ; Jiao, L.C.
Author_Institution :
Key Lab. of Intell. Perception & Image Understanding of Minist. of Educ., Xidian Univ., Xi´an, China
Volume :
48
Issue :
20
fYear :
2012
Firstpage :
1263
Lastpage :
1265
Abstract :
Based on the particle swarm optimisation algorithm, an ARD-FS system integrating the automatic relevance determination (ARD) and the feature selection (FS) for a Gaussian process classifier (GPC) is proposed. The ARD-FS system aims to reduce the complexity of the GPC and simultaneously improve the classification accuracy. It is applied to the hyperspectral images and experimental results demonstrate its good performance for hyperspectral image classification even with very limited labelled samples but high-dimensional features.
Keywords :
Gaussian processes; image classification; learning (artificial intelligence); particle swarm optimisation; ARD; ARD-FS system; Gaussian process classifier; PSO-based automatic relevance determination; feature selection system; hyperspectral image classification; particle swarm optimisation algorithm;
fLanguage :
English
Journal_Title :
Electronics Letters
Publisher :
iet
ISSN :
0013-5194
Type :
jour
DOI :
10.1049/el.2012.0539
Filename :
6329559
Link To Document :
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