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Proceedings Paper

An image clutter metric based on multidirectional difference hash
Author(s): Yufei Zhao; Yong Song; Muhammad Sulaman; Xu Li; Zhengkun Guo; Xin Yang; Fengning Wang
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Paper Abstract

Quantification of image clutter plays an important role in predicting target acquisition performances of a photoelectric imaging system due to the strong effect of optoelectronic image clutter. Accuracy in predicting the targeting performance of previous reported clutter metrics was relatively low because of disadvantages, such as lack of ability to accurately quantify the image with complex clutters and threshold selection problem. To address this problem, a novel multidirectionaldifference-Hash-based image clutter metric is proposed in this paper. Initially, an image similarity measure method based on multidirectional difference hash is established. Then, this method is applied to the quantification of image clutter, and an MDHash-based image clutter metric is obtained. Experimental results show that the proposed clutter metric correlates effectively with probability of detection, false alarm rate, and search time of observers.

Paper Details

Date Published: 31 January 2020
PDF: 6 pages
Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114272F (31 January 2020);
Show Author Affiliations
Yufei Zhao, Beijing Institute of Technology (China)
Beijing Key Lab. for Precision Optoelectronic Measurement Instrument and Technoogy (China)
Yong Song, Beijing Institute of Technology (China)
Beijing Key Lab. for Precision Optoelectronic Measurement Instrument and Technoogy (China)
Muhammad Sulaman, Beijing Institute of Technology (China)
Beijing Key Lab. for Precision Optoelectronic Measurement Instrument and Technoogy (China)
Xu Li, Beijing Institute of Technology (China)
Beijing Key Lab. for Precision Optoelectronic Measurement Instrument and Technoogy (China)
Zhengkun Guo, Beijing Institute of Technology (China)
Beijing Key Lab. for Precision Optoelectronic Measurement Instrument and Technoogy (China)
Xin Yang, Beijing Institute of Technology (China)
Beijing Key Lab. for Precision Optoelectronic Measurement Instrument and Technoogy (China)
Fengning Wang, Beijing Institute of Technology (China)
Beijing Key Lab. for Precision Optoelectronic Measurement Instrument and Technoogy (China)


Published in SPIE Proceedings Vol. 11427:
Second Target Recognition and Artificial Intelligence Summit Forum
Tianran Wang; Tianyou Chai; Huitao Fan; Qifeng Yu, Editor(s)

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