Detection of super wide-field infrared target based on spatial-temporal fusion processing

HUANG Fu-yu; SHEN Xue-ju; LIU Xu-min; CUI Tie-cheng

doi:10.3788/OPE.20152308.2328

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Detection of super wide-field infrared target based on spatial-temporal fusion processing

更新时间：2020-08-12

- Detection of super wide-field infrared target based on spatial-temporal fusion processing
- Optics and Precision Engineering Vol. 23, Issue 8, Pages: 2328-2338(2015)
- 作者机构：
  
  1. 军械工程学院电子与光学工程系,河北石家庄,050003
  2. 中国人民解放军63861部队,吉林白城,137001
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152308.2328
  CLC： TN215;TP391.4
- Received：09 December 2014，
  
  Revised：12 February 2015，
  
  Published：25 August 2015
- 稿件说明：
移动端阅览
黄富瑜, 沈学举, 刘旭敏等. 基于空时域融合处理检测超大视场红外目标[J]. 光学精密工程, 2015,23(8): 2328-2338

HUANG Fu-yu, SHEN Xue-ju, LIU Xu-min etc. Detection of super wide-field infrared target based on spatial-temporal fusion processing[J]. Editorial Office of Optics and Precision Engineering, 2015,23(8): 2328-2338
黄富瑜, 沈学举, 刘旭敏等. 基于空时域融合处理检测超大视场红外目标[J]. 光学精密工程, 2015,23(8): 2328-2338 DOI： 10.3788/OPE.20152308.2328.

HUANG Fu-yu, SHEN Xue-ju, LIU Xu-min etc. Detection of super wide-field infrared target based on spatial-temporal fusion processing[J]. Editorial Office of Optics and Precision Engineering, 2015,23(8): 2328-2338 DOI： 10.3788/OPE.20152308.2328.

摘要

针对超大视场红外凝视成像系统用于目标检测时存在的背景复杂、杂波干扰多、目标信息少等问题

提出了基于空时域融合处理的目标检测方法。该方法在空域部分优化设计Robinson算子

完成单帧图像的目标初始检测;然后结合超大视场成像特性

利用基于天地线检测的图像区域自动划分和空域虚警抑制方法

有效滤除非目标检测区中的疑似目标。在时域部分则兼顾目标时域特征

采用基于时域多特征约束的邻域判决法对真实目标进行时域确认。开展了月空背景下的空中目标检测试验

验证了本文算法的有效性。试验表明:经空域部分处理后

原始图像中的背景杂波干扰大大减少

目标局部信噪比提高了1.3倍以上

而且疑似目标数目减少了70%;经时域部分处理后

可成功检测出红外弱小目标

并输出其轨迹

检测概率在95%以上

而虚警率不足1.5%

最低目标检测信噪比为2.86。实验表明:本文方法适用于超大视场图像的红外弱小目标检测

对地物背景、恒亮孤立点源、瞬时强噪声等干扰有较强的抑制能力

对点状运动目标有良好的检测效能。

Abstract

When a super wide-field infrared staring system is used to detect a target

it may show complex background

more noise jamming and little target information. Therefore

this paper proposes a spatial-temporal fusion algorithm. In spatial processing

the single image was filtered by an improved Robinson operator

and the primary detection of the target was carried out. Then

the image auto-partition and spatial false-alarm suppression were presented to eliminate the suspected target from a non-target detection region. In temporal processing

the temporal characteristics of the target was considered

the neighbor judgment method was improved to confirm the real target. A detection experiment for the space target was carried out in a moon light

and this proposed algorithm was vilified. It shows that the background interference of original image is suppressed greatly

the local Signal to Noise Ratio(SNR) can be improved more than 1.3 times

the false target number decreases by 70% after spatial processing. Moreover

the infrared weak target is detected successfully with the detection probability of higher than 95%

the false-alarm probability of less than 1.5% and the minimum detection SNR of 2.86 after spatial processing. It concludes that this algorithm is suitable for the infrared weak target detection of super wide-field image and can detect the moving point targets effectively.It has a good suppression effect for background interference

isolated point sources and instantaneous noise.

关键词

Keywords

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