J4 ›› 2014, Vol. 41 ›› Issue (1): 13-17.doi: 10.3969/j.issn.1001-2400.2014.01.003

• 研究论文 • 上一篇    下一篇

检测红外弱小目标的对比滤波时域廓线算法

董维科;张建奇;邵晓鹏;刘德连   

  1. (西安电子科技大学 物理与光电工程学院,陕西 西安  710071)
  • 收稿日期:2012-12-06 出版日期:2014-02-20 发布日期:2014-04-02
  • 作者简介:董维科(1973-),男,副教授,硕士, E-mail:wkdong@mail.xidian.edu.cn.
  • 基金资助:

    教育部基本科研业务费资助项目(50511050005);国家部委基金资助项目(9140A01060110DZ0125)

Temporal profile algorithm based on comparison filtering for detection of the infrared dim small target

DONG Weike;ZHANG Jianqi;SHAO Xiaopeng;LIU Delian   

  1. (School of Physics and Optoelectronic Engineering, Xidian Univ., Xi'an  710071, China)
  • Received:2012-12-06 Online:2014-02-20 Published:2014-04-02

摘要:

针对弱小目标与云边缘杂波的运动速度相当时,传统时域廓线算法的检测性能将会出现明显下降.文中提出一种对比滤波的时域廓线算法.针对传统方法出现虚警的情况,该方法在分析弱小目标、云边缘杂波以及平稳背景3类像素点时域特性的基础之上,首先利用时域廓线特性抑制平稳背景;然后依据云边缘杂波像素在空域连续,而弱小目标像素在空域孤立的特性,构造空域对比滤波器,并使用对比滤波器对去除平稳背景的图像数据进行滤波;最后再进行时域廓线的驻点连线滤波,以实现对弱小目标的检测.仿真结果表明,该算法能明显消除与弱小目标运动速度相当的云边缘杂波虚警,提高了弱小目标的检测概率.

关键词: 弱小目标, 检测, 对比滤波, 时域廓线

Abstract:

The detection performance of the traditional temporal profile algorithm deteriolates when the dim small target has a velocity correspmding to equivalent that of cloud edge clutters. This paper proposes a temporal profile algorithm based on comparison filtering as a responding method to the fake-alarm occurrence existing in the traditional detection algorithm. Based on the analysis of the time domain characteristics of the dim small target, cloud edge clutters as well as the stationary background, the characteristic of the temporal profile is adopted to restrain the stationary background, and then the spatial domain comparison filter is structured based on the fact that the pixels of the cloud edge clutters are continuous in spatial domain while the pixels of the dim small target are discrete, and the images after removal of the static background are filtered by the comparison filter; lastly, the connecting line of the stagnation points (CLSP) based filtering is used to realize the detection of the dim small target. Simulation data show that this algorithm can significantly eliminate the fake-alarm caused by the cloud edge clutters with an equivalent velocity of the target, thus further improving the detection probability of the dim small target.

Key words: dim small target, detection, comparison filtering, temporal profile