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Proceedings Paper

Complex background suppression using global-local registration strategy for the detection of small-moving target on moving platform
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Paper Abstract

Target detection is a very important and basic problem of computer vision and image processing. The most often case we meet in real world is a detection task for a moving-small target on moving platform. The commonly used methods, such as Registration-based suppression, can hardly achieve a desired result. To crack this hard nut, we introduce a Global-local registration based suppression method. Differ from the traditional ones, the proposed Global-local Registration Strategy consider both the global consistency and the local diversity of the background, obtain a better performance than normal background suppression methods. In this paper, we first discussed the features about the small-moving target detection on unstable platform. Then we introduced a new strategy and conducted an experiment to confirm its noisy stability. In the end, we confirmed the background suppression method based on global-local registration strategy has a better perform in moving target detection on moving platform.

Paper Details

Date Published: 19 February 2018
PDF: 6 pages
Proc. SPIE 10608, MIPPR 2017: Automatic Target Recognition and Navigation, 106080G (19 February 2018); doi: 10.1117/12.2285155
Show Author Affiliations
Tianhao Zou, Huazhong Univ. of Science and Technology (China)
Zhengrong Zuo, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 10608:
MIPPR 2017: Automatic Target Recognition and Navigation
Jianguo Liu; Jayaram K. Udupa; Hanyu Hong, Editor(s)

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