OBJECT RECOGNITION IN URBAN HYPERSPECTRAL IMAGES USING BINARY PARTITION TREE REPRESENTATION

被引：8
|
作者：
Valero, Silvia [1 ,2 ,3 ]
Salembier, Philippe [2 ]
Chanussot, Jocelyn [3 ,4 ]
机构：
[1] Univ Toulouse, CNRS, CNES, CESBIO,IRD,UMR 5126, Toulouse, France
[2] Tech Univ Catalonia, Barcelona, Spain
[3] Grenoble Inst Technol, Dept Signal & Image, GIPSA, Grenoble, France
[4] Univ Iceland, Fac Elect & Comp Engn, IS-101 Reykjavik, Iceland
来源：
2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2013年
关键词：
Object detection; Region-based image analysis; BPT; hyperspectral;
D O I：
10.1109/IGARSS.2013.6723734
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this work, an image representation based on Binary Partition Tree is proposed for object detection in hyperspectral images. The BPT representation defines a search space for constructing a robust object identification scheme. Spatial and spectral information are integrated in order to analyze hyperspectral images with a region-based perspective. Experimental results demonstrate the good performances of this BPT-based approach.
引用
收藏
页码：4098 / 4101
页数：4
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