An image clutter metric based on multidirectional difference hash

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationSecond Target Recognition and Artificial Intelligence Summit Forum
EditorsWang Tianran, Chai Tianyou, Fan Huitao, Yu Qifeng
PublisherSPIE
ISBN (Electronic)9781510636316
DOIs
Publication statusPublished - 2020
Event2nd Target Recognition and Artificial Intelligence Summit Forum 2019 - Shenyang, China
Duration: 28 Aug 201930 Aug 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11427
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2nd Target Recognition and Artificial Intelligence Summit Forum 2019
Country/TerritoryChina
CityShenyang
Period28/08/1930/08/19

Keywords

  • Difference hash
  • Image clutter metric
  • Image similarity measure
  • Targeting performance

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