Complexity estimation of image sequence for automatic target track

doi:10.21629/JSEE.2019.04.05

Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (4): 672-683.doi: 10.21629/JSEE.2019.04.05

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Complexity estimation of image sequence for automatic target track

Xiaotian WANG*(), Kai ZHANG(), Jie YAN()

School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China

Received:2019-01-03 Online:2019-08-01 Published:2019-08-29
Contact: Xiaotian WANG E-mail:18710993786@163.com;singlechip@163.com;yanjie@nwpu.edu.cn
About author:WANG Xiaotian was born in 1989. He received his B.S. degree in 2013 from North China Institute of Aerospace Engineering. He received his M.S. degree from School of Electronics and Information, Northwestern Polytechnical University in 2016. He is a Ph.D. candidate with the School of Astronautics, Northwestern Polytechnical University. His research interests are object detection, object tracking and image quality evaluation. E-mail:18710993786@163.com|ZHANG Kai was born in 1979. He received his Ph.D. degree from School of Astronautics, Northwestern Polytechnical University in 2009. As an associate professor, he is working in School of Astronautics, Northwestern Polytechnical University. His research interests are guidance, navigation and control. E-mail:singlechip@163.com|YAN Jie was born in 1960. He received his Ph.D. degree from School of Astronautics, Northwestern Polytechnical University in 1988. He is currently working as a professor and Ph.D. candidate supervisor in School of Astronautics, Northwestern Polytechnical University. His research interests are flight control, guidance, system simulation and aircraft design. E-mail:yanjie@nwpu.edu.cn
Supported by:
the National Natural Science Foundation of China(61703337);Shanghai Aerospace Science and Technology Innovation Fund(SAST2017-082);This work was supported by the National Natural Science Foundation of China (61703337) and Shanghai Aerospace Science and Technology Innovation Fund (SAST2017-082)

Abstract

Abstract:

In the field of automatic target recognition and tracking, traditional image complexity metrics, such as statistical variance and signal-to-noise ratio, all focus on single-frame images. However, there are few researches about the complexity of image sequence. To solve this problem, a criterion of evaluating image sequence complexity is proposed. Firstly, to characterize this criterion quantitatively, two metrics for measuring the complexity of image sequence, namely feature space similarity degree of global background (FSSDGB) and feature space occultation degree of local background (FSODLB) are developed. Here, FSSDGB reflects the ability of global background to introduce false alarms based on feature space, and FSODLB represents the difference between target and local background based on feature space. Secondly, the feature space is optimized by the grey relational method and relevant features are removed so that FSSDGB and FSODLB are more reasonable to establish complexity of single-frame images. Finally, the image sequence complexity is not a linear sum of the single-frame image complexity. Target tracking errors often occur in high-complexity images and the tracking effect of low-complexity images is very well. The nonlinear transformation based on median (NTM) is proposed to construct complexity of image sequence. The experimental results show that the proposed metric is more valid than other metrics, such as sequence correlation (SC) and interframe change degree (IFCD), and it is highly relevant to the actual performance of automatic target tracking algorithms.

Key words: complexity of image sequence, feature space similarity degree of global background (FSSDGB), feature space occultation degree of local background (FSODLB), grey relational method, nonlinear transformation based on median (NTM)

Xiaotian WANG, Kai ZHANG, Jie YAN. Complexity estimation of image sequence for automatic target track[J]. Journal of Systems Engineering and Electronics, 2019, 30(4): 672-683.

Figures/Tables 12

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Index	TBC	TIR	ETB	KSZ	GDC
TBC	1	0.968 4	0.335 8	0.534 1	0.493 6
TIR	—	1	0.463 2	0.624 3	0.362 1
ETB	—	—	1	0.956 2	0.586 4
KSZ			—	1	0.358 7
GDC	—	—	—		1

Index	COM	TSD	LTW	ENT	ACL	IFCDTGL	IFCDTML	POT
COM	1	0.370 4	0.609 1	0.432 4	0.886 6	0.426 8	0.489 4	0.603 5
TSD	—	1	0.502 9	0.725 6	0.403 6	0.658 4	0.647 2	0.506 4
LTW	—	—	1	0.601 7	0.652 5	0.635 4	0.618 3	0.921 6
ENT	—	—	—	1	0.456 5	0.738 3	0.808 2	0.605 6
ACL	—	—	—	—	1	0.512 2	0.511 5	0.646 3
IFCDTGL	—	—	—	—	—	1	0.535	0.687 3
IFCDTML	—	—	—	—	—	—	1	0.630 3
POT	—	—	—	—	—	—	—	1

Index	FSSDGB	FSODLB	Image complexity
Fig. 5(a)	0.054	0.303	0.092
Fig. 5(b)	0.157	0.354	0.218
Fig. 5(c)	0.945	0.250	0.395
Fig. 5(d)	0.773	0.778	0.775

Complexity estimation of image sequence for automatic target track

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