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Infrared small target detection based on multiscale center-surround contrast measure
Author(s): Hao Fu; Yunli Long; Ran Zhu; Wei An
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Paper Abstract

Infrared(IR) small target detection plays a critical role in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some difficulties remained to the clutter environment. According to the principle of human discrimination of small targets from a natural scene that there is a signature of discontinuity between the object and its neighboring regions, we develop an efficient method for infrared small target detection called multiscale centersurround contrast measure (MCSCM). First, to determine the maximum neighboring window size, an entropy-based window selection technique is used. Then, we construct a novel multiscale center-surround contrast measure to calculate the saliency map. Compared with the original image, the MCSCM map has less background clutters and noise residual. Subsequently, a simple threshold is used to segment the target. Experimental results show our method achieves better performance.

Paper Details

Date Published: 10 April 2018
PDF: 8 pages
Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106150I (10 April 2018); doi: 10.1117/12.2304596
Show Author Affiliations
Hao Fu, National Univ. of Defense Technology (China)
Yunli Long, National Univ. of Defense Technology (China)
Ran Zhu, National Univ. of Defense Technology (China)
Wei An, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 10615:
Ninth International Conference on Graphic and Image Processing (ICGIP 2017)
Hui Yu; Junyu Dong, Editor(s)

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