DocumentCode :
1845104
Title :
Multi-feature model analysis-based target identification for remote sensing image
Author :
Lin Qi ; Jinfeng Yang ; Yuchun Wen ; Pengfei Ma ; Chenghua Xu ; Hui Hao
Author_Institution :
Tianjin Key Lab. for Adv. Signal Process., Civil Aviation Univ. of China, Tianjin, China
Volume :
1
fYear :
2012
fDate :
21-25 Oct. 2012
Firstpage :
771
Lastpage :
774
Abstract :
Recently, target identification has become a key topic due to the richness of nature resources contained in high-resolution remote sensing image. Many algorithms have been proposed in this aspect. In order to reduce algorithmic complexity and shorten computing cost, a multi-feature analysis model is proposed to identify targets in remote sensing images. The originality of the method includes two aspects. (1) City planning diagram, which is a vector file in the term of polygons of indispensable attributes, is used for image partition. (2) Multiple features are modeled, and then an identification rule is developed based on the model and minimum distance classification. Experimental results show that the proposed method is reliable in performing target identification.
Keywords :
computational complexity; feature extraction; geophysical image processing; image classification; image resolution; object recognition; remote sensing; town and country planning; algorithmic complexity reduction; city planning diagram; feature modeling; high-resolution remote sensing image; identification rule; image partition; minimum distance classification; model classification; multifeature model analysis; target identification; vector file; city planning diagram; model file; multi-feature; target identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing (ICSP), 2012 IEEE 11th International Conference on
Conference_Location :
Beijing
ISSN :
2164-5221
Print_ISBN :
978-1-4673-2196-9
Type :
conf
DOI :
10.1109/ICoSP.2012.6491601
Filename :
6491601
Link To Document :
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