DocumentCode :
1952538
Title :
Salient target detection in hyperspectral images using spectral saliency
Author :
Yan Cao ; Jing Zhang ; Qi Tian ; Li Zhuo ; Qianlan Zhou
Author_Institution :
Signal & Inf. Process. Lab., Beijing Univ. of Technol., Beijing, China
fYear :
2015
fDate :
12-15 July 2015
Firstpage :
1086
Lastpage :
1090
Abstract :
The researches on saliency detection for common images have been thoroughly explored in recent years, but little attention has been paid to hyperspectral images. However, salient region detection can contribute to finding significant targets in hyperspectral images. In this paper, spectral saliency is introduced to the spectral domain for detecting targets in hyperspectral images, which are computed by expanding the Itti´s visual attention model. Firstly, spatial and spectral features are extracted from hyperspectral image. The conspicuity feature of the first three principal components, orientations, spectral angle and visible spectral band opponent are computed to sum into a saliency map. Finally, salient targets are detected by winner-take-all strategy finding the region with the highest value in the saliency map. Experimental results show that the proposed method have better effectiveness of target detection compared with the method based on RGB image and visible spectrum.
Keywords :
feature extraction; hyperspectral imaging; object detection; principal component analysis; spectral analysis; Itti visual attention model; feature extraction; hyperspectral image; principal component; salient region detection; salient target detection; spectral saliency; Decision support systems; Erbium; Indexes; Hyperspectral imagery; saliency map; salient target detection; spectral saliency; visual attention model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal and Information Processing (ChinaSIP), 2015 IEEE China Summit and International Conference on
Conference_Location :
Chengdu
Type :
conf
DOI :
10.1109/ChinaSIP.2015.7230572
Filename :
7230572
Link To Document :
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