LS-SVM based dim and small infrared target dualband fusion detection

Yuqiu Sun; Shalan Li; Jinwen Tian; Jian Liu

doi:10.1117/12.774861

10 November 2007 LS-SVM based dim and small infrared target dualband fusion detection

Yuqiu Sun, Shalan Li, Jinwen Tian, Jian Liu

Proceedings Volume 6795, Second International Conference on Space Information Technology; 67953J (2007) https://doi.org/10.1117/12.774861
Event: Second International Conference on Spatial Information Technology, 2007, Wuhan, China

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.

Citation Download Citation

Yuqiu Sun, Shalan Li, Jinwen Tian, and Jian Liu "LS-SVM based dim and small infrared target dualband fusion detection", Proc. SPIE 6795, Second International Conference on Space Information Technology, 67953J (10 November 2007); https://doi.org/10.1117/12.774861

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