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Infrared small target detection based on an image-patch tensor model

delete2019-06-01
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PRE
AI
X
Xiangyue Zhang *
罗海波 cover
罗海波 (Haibo Luo)
B
Bin Hui
Z
Zheng Chang
J
Junchao Zhang
DOI:10.1016/j.infrared.2019.03.009delete
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Abstract

Abstract

En 中文
Infrared small target detection under complex background has been applied to many fields and is still a challenging problem. In this paper, a small target detection method base on an image-patch tensor (IPT) model is proposed. Firstly, considering the structural relationship between pixels, the original single-frame image is constructed as a new image-patch tensor. Secondly, based on the correlation of the background image patch and the sparsity of the target image patch, the small target detection problem can be transformed into an optimization problem of separating the low-rank part and the sparse part of the tensor. Finally, after simple post filtering, the target is separated adaptively. Experimental results show that the proposed method can detect the small target precisely and can keep a higher signal-to-clutter ratio (SCR). What's more, compared with other methods, the proposed method shows better detection performance.
Keywords:
Small target detection
Image patch
Tensor
Sparsity
Infrared image
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

I
Infrared Physics and Technology
IF:
3.4
Papers:
5.8K
Citations:
1.2W

Organization

C
chinese academy of sciences
Scholars:
56.3W
Papers: 44.8W
Citations: 704