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Proceedings Paper

LS-SVM based dim and small infrared target dualband fusion detection
Author(s): Yuqiu Sun; Shalan Li; Jinwen Tian; Jian Liu
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Paper Abstract

Aiming at the characters of weak and small targets in infrared images, an algorithm based on Least Squares Support Vector Machines (LS-SVM) is presented to fuse long-wave and mid-wave infrared images and detect targets. Image intensity surfaces for the neighborhood of every pixel of the original long-wave infrared image and mid-wave infrared are well-fitted by mapped LS-SVM respectively. And long-wave and mid-wave infrared image gradient images are obtained by LS-SVM based on radial basis kernels function. Fusion rule is set up according to the features of gradient images. At last, segment fused image and targets can be detected with contrast threshold. Compared with wavelet fusion detection algorithm and morphological fusion detection algorithm, when a target is affected by baits, the experimental results demonstrate that the proposed approach in the paper based on LS-SVM to fuse and detect weak and small target is reliable and efficient.

Paper Details

Date Published: 10 November 2007
PDF: 7 pages
Proc. SPIE 6795, Second International Conference on Space Information Technology, 67953J (10 November 2007); doi: 10.1117/12.774861
Show Author Affiliations
Yuqiu Sun, Yangtze Univ. (China)
Huazhong Univ. of Science and Technology (China)
Shalan Li, Air Force Radar Academy (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)
Jian Liu, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 6795:
Second International Conference on Space Information Technology
Cheng Wang; Shan Zhong; Jiaolong Wei, Editor(s)

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