Infrared small target detection based on multiscale center-surround contrast measure

Hao Fu; Yunli Long; Ran Zhu; Wei An

doi:10.1117/12.2304596

10 April 2018 Infrared small target detection based on multiscale center-surround contrast measure

Hao Fu, Yunli Long, Ran Zhu, Wei An

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106150I (2018) https://doi.org/10.1117/12.2304596
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

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.

Citation Download Citation

Hao Fu, Yunli Long, Ran Zhu, and Wei An "Infrared small target detection based on multiscale center-surround contrast measure", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106150I (10 April 2018); https://doi.org/10.1117/12.2304596

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