Sparse-representation-based clutter metric

被引:11
|
作者
Yang, Cui [1 ]
Wu, Jie [1 ]
Li, Qian [1 ]
Zhang, Jian-Qi [1 ]
机构
[1] Xidian Univ, Sch Tech Phys, Xian 710071, Shaanxi, Peoples R China
基金
美国国家科学基金会;
关键词
DETECTION PROBABILITY; RELATIVE CLUTTER; PERFORMANCE; SEARCH;
D O I
10.1364/AO.50.001601
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Background clutter is becoming one of the most important factors affecting the target acquisition performance of electro-optical imaging systems. A novel clutter metric based on sparse representation is proposed in this paper. Based on sparse representation, the similarity vector is defined to describe the similarity between the background and the target in the feature domain, which is a typical feature of the background clutter. This newly proposed metric is applied to the Search_2 data set, and the experiment results show that its prediction correlates well with the detection probability of observers. (C) 2011 Optical Society of America
引用
收藏
页码:1601 / 1605
页数:5
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