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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.
Yuqiu Sun,Shalan Li,Jinwen Tian, andJian 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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Yuqiu Sun, Shalan Li, Jinwen Tian, 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