Infrared dim-small target detection based on an improved multiscale fractal feature

doi:10.3788/OPE.20202806.1375

CIOMP OpenIR

	Infrared dim-small target detection based on an improved multiscale fractal feature
	Y. Gu,J. Liu,H.-H. Shen,D.-L. Peng and Y. Xu
	2020
发表期刊	Guangxue Jingmi Gongcheng/Optics and Precision Engineering
ISSN	1004924X
卷号	28 期号:6 页码:1375-1386
摘要	To improve the accuracy and real-time performance of infrared (IR) dimsmall target detection, an IR dimsmall object detection algorithm based on an improved multi-scale fractal feature was presented. Computational analysis of the multi-scale fractal feature related to the fractal parameter K (MFFK), which was used for IR image enhancement in the algorithm, was performed. First, an improved multi-scalefractal feature (IMFFK) was presented to perform image enhancement after substituting the equation for computing fractal dimension into the equation for computing MFFK using the covering-blanket method. Thereafter, a computationally efficient IR dimsmall target detection algorithm was presented, in which the computation of IMFFK was simplified and an adaptive threshold was used to segment targets of interest from the background. Finally, the effect of primary parameters on image enhancement and computational cost was analyzed based on the simulation images. The IR real-world images were subsequently used to evaluate the detection performance of the proposed algorithm, and comparisons with state-of-the-art detection algorithms based on local contrast measureare performed. The proposed algorithm was capable of simultaneously detecting dimsmall and large targets in an IR image, irrespective of whether the targets were bright or dark, even though false alarms were detected in some scenarios. It is also capable of reachingapproximately 30 frames per second for low-resolution IR images (320240). The proposed algorithm exhibitssatisfactory applicability and can be used to detect targets with high local contrast in an image. 2020, Science Press. All right reserved.
DOI	10.3788/OPE.20202806.1375
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收录类别	EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/64616
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	Y. Gu,J. Liu,H.-H. Shen,D.-L. Peng and Y. Xu. Infrared dim-small target detection based on an improved multiscale fractal feature[J]. Guangxue Jingmi Gongcheng/Optics and Precision Engineering,2020,28(6):1375-1386.
APA	Y. Gu,J. Liu,H.-H. Shen,D.-L. Peng and Y. Xu.(2020).Infrared dim-small target detection based on an improved multiscale fractal feature.Guangxue Jingmi Gongcheng/Optics and Precision Engineering,28(6),1375-1386.
MLA	Y. Gu,J. Liu,H.-H. Shen,D.-L. Peng and Y. Xu."Infrared dim-small target detection based on an improved multiscale fractal feature".Guangxue Jingmi Gongcheng/Optics and Precision Engineering 28.6(2020):1375-1386.

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