An image clutter metric based on multidirectional difference hash

Yufei Zhao; Yong Song; Muhammad Sulaman; Xu Li; Zhengkun Guo; Xin Yang; Fengning Wang

doi:10.1117/12.2552348

31 January 2020 An image clutter metric based on multidirectional difference hash

Yufei Zhao, Yong Song, Muhammad Sulaman, Xu Li, Zhengkun Guo, Xin Yang, Fengning Wang

Proceedings Volume 11427, Second Target Recognition and Artificial Intelligence Summit Forum; 114272F (2020) https://doi.org/10.1117/12.2552348
Event: Second Target Recognition and Artificial Intelligence Summit Forum, 2019, Changchun, China

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.

Citation Download Citation

Yufei Zhao, Yong Song, Muhammad Sulaman, Xu Li, Zhengkun Guo, Xin Yang, and Fengning Wang "An image clutter metric based on multidirectional difference hash", Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114272F (31 January 2020); https://doi.org/10.1117/12.2552348

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