Unsupervised SAR Imagery Segmentation Based on SVDD

被引：0

作者：

Zhang, XiongMei ^{[1
]}

Song, JianShe ^{[1
]}

Yi, ZhaoXiang ^{[1
]}

Wang, RuiHua ^{[1
]}

机构：

[1] Xian Res Inst High Tech, Xian 710025, Peoples R China

来源：

ADVANCES IN MULTIMEDIA, SOFTWARE ENGINEERING AND COMPUTING, VOL 1 | 2011年 / 128卷

关键词：

SAR imagery; support vector domain description(SVDD); unsupervised segmentation; texture feature; Bayesian decision;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Based on the extraction of texture features, the Bayesian decision rule is employed to identify the decision threshold that separates the target from the background in the magnitude image. Then, the training samples for the SVDD classifier are automatically selected and used to train the classifier. Finally, the trained SVDD classifier is used to classify the rest pixels of the thresholding process. Experimental results obtained on real and simulated SAR imageries demonstrate the effectiveness of the proposed method.

引用

页码：25 / 31

页数：7

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