Infrared images target detection based on background modeling in the discrete cosine domain

Han Ye; Jihong Pei

doi:10.1117/12.2285785

19 February 2018 Infrared images target detection based on background modeling in the discrete cosine domain

Han Ye, Jihong Pei

Proceedings Volume 10608, MIPPR 2017: Automatic Target Recognition and Navigation; 106080J (2018) https://doi.org/10.1117/12.2285785
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China

Abstract

Background modeling is the critical technology to detect the moving target for video surveillance. Most background modeling techniques are aimed at land monitoring and operated in the spatial domain. A background establishment becomes difficult when the scene is a complex fluctuating sea surface. In this paper, the background stability and separability between target are analyzed deeply in the discrete cosine transform (DCT) domain, on this basis, we propose a background modeling method. The proposed method models each frequency point as a single Gaussian model to represent background, and the target is extracted by suppressing the background coefficients. Experimental results show that our approach can establish an accurate background model for seawater, and the detection results outperform other background modeling methods in the spatial domain.

Citation Download Citation

Han Ye and Jihong Pei "Infrared images target detection based on background modeling in the discrete cosine domain", Proc. SPIE 10608, MIPPR 2017: Automatic Target Recognition and Navigation, 106080J (19 February 2018); https://doi.org/10.1117/12.2285785

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