Multi-class target recognition based on adaptive feature selection

被引：2

作者：

Wang, Yuehuan ^{[1
,2
]}

Yao, Wei ^{[1
]}

Song, Yunfeng ^{[1
]}

Sang, Nong ^{[2
]}

Zhang, Tianxu ^{[2
]}

机构：

[1] Huazhong Univ Sci & Technol, Inst Pattern Recognit & AI, Wuhan 430074, Peoples R China

[2] Natl Key Lab Sci & Tech, Multi Spectral Informat Proc Technol, Wuhan 430074, Peoples R China

来源：

AUTOMATIC TARGET RECOGNITION XX; ACQUISITION, TRACKING, POINTING, AND LASER SYSTEMS TECHNOLOGIES XXIV; AND OPTICAL PATTERN RECOGNITION XXI | 2010年 / 7696卷

关键词：

remote sensing image; adaptive feature selection; multiclass target recognition;

D O I：

10.1117/12.850649

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

In this paper, a new approach of multi-class target recognition is proposed for remote sensing image analysis. A multi-class feature model is built, which is based on sharing features among classes. In order to make the recognition process efficient, we adopted the idea of adaptive feature selection. In each layer of the integrated feature model, the most salient and stable feature are selected first, and then the less ones. Experiments demonstrated the approach proposed is efficient in computation and is adaptive to scene variation.

引用

页数：9

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