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Proceedings Paper

Image metric analysis of laser jamming effect based on edge strength similarity and gray mean square error
Author(s): Li Shao; Yun-long Wu
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Paper Abstract

Laser jamming plays an important role in the countermeasure to optoelectronic imaging systems. The influence of laser jamming on optoelectronic imaging systems was introduced briefly. In order to evaluate the performance of laser jamming objectively, quantitatively and precisely, a comprehensive image metric combining the edge strength similarity(ESM) with gray mean square error(MSE) was proposed from the view of laser jamming images. The computation methods of edge strength similarity and gray mean square error were provided. The metric computed the edge strength similarity between target image and background image, and gray mean square error between target image and reference image comprehensively to evaluate the laser jamming performance quantitatively. Computing the edge strength similarity between target image and background image could be viewed as a local evaluation metric, and computing the ray mean square error between target image and reference image could be viewed as global evaluation metric. The two metric was combined to evaluate the performance of laser jamming comprehensively. Experimental results of laser jamming in and out the field of view showed that the proposed metric could realize quantitative appraisal of laser jamming performance on optoelectronic imaging systems.

Paper Details

Date Published: 25 October 2016
PDF: 7 pages
Proc. SPIE 9686, 8th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices, 96860O (25 October 2016); doi: 10.1117/12.2243215
Show Author Affiliations
Li Shao, Hefei Electronic Institute (China)
Yun-long Wu, Hefei Electronic Institute (China)


Published in SPIE Proceedings Vol. 9686:
8th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices
Yadong Jiang; Bernard Kippelen; Junsheng Yu, Editor(s)

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