REMOTE SENSING IMAGE CLASSIFICATION OF GEOEYE-1 HIGH-RESOLUTION SATELLITE
(0) Networks play the role of a high-level language,as is seen in Artificial Intelligence and statistics,because networks are used to build complex model from simple components.These years,Bayesian Networks,one of probabilistic networks,are a powerful data mining technique for handling uncertainty in complex domains.In this paper,we apply Bayesian Networks Augmented Naive Bayes (BAN) to texture classification of High-resolution satellite images and put up a new method to construct the network topology structure in terms of training accuracy based on the training samples.In the experiment,we choose GeoEye-1 satellite images.Experimental results demonstrate BAN outperform than NBC in the overall classification accuracy.Although it is time consuming,it will be an attractive and effective method in the future.
Texture Classification Pattern Recognition High-resolution Satellite Image
YANG BOGANG XIN YU
Beijing Institute of Surveying and Mapping,Beijing,100038,China;Beijing Key Laboratory of Urban Spatial Information Engineering,Beijing,100038,China,
国内会议
苏州
英文
325-328
2014-05-14（万方平台首次上网日期，不代表论文的发表时间）