Poster + Paper
21 August 2020 Infrared small target detection based on fusion of multiple saliency information
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Conference Poster
Abstract
To improve the detection rate of small target in infrared image, this paper proposes an infrared small target detection algorithm based on the fusion of multiple saliency information, which combines local contrast measure (LCM), curvature filtering and motion saliency. Firstly, three saliency maps of the infrared image are calculated separately to prepare for the next advantages integration. Then, to improve the contrast of the target, the LCM saliency map and curvature saliency map are filtered according to the motion saliency value. Finally, the fusion weight is determined by the background suppression factor of the saliency map so that the fusion saliency map is obtained. Experimental results show that the proposed infrared small target algorithm outperforms other comparing methods in terms of detection capability.
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Chao Ma, Guohu Gu, Minjie Wan, Congcong Song, and He Zhang "Infrared small target detection based on fusion of multiple saliency information", Proc. SPIE 11510, Applications of Digital Image Processing XLIII, 115102B (21 August 2020); https://doi.org/10.1117/12.2566245
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KEYWORDS
Detection and tracking algorithms

Target detection

Infrared imaging

Infrared detectors

Image fusion

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