Pre-detection method for small infrared target

JIN Yong-liang; WANG Yan-jie; LIU Yan-ying; HUANG Ji-peng

doi:10.3788/OPE.20122001.0171

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Pre-detection method for small infrared target

Article | 更新时间：2020-08-12

- Pre-detection method for small infrared target
- Optics and Precision Engineering Vol. 20, Issue 1, Pages: 171-178(2012)
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院研究生院北京,100039
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20122001.0171
  CLC： TP391.4
- Received：23 May 2011，
  
  Revised：21 June 2011，
  
  Published Online：25 January 2012，
  
  Published：25 January 2012
- 稿件说明：
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靳永亮, 王延杰, 刘艳滢, 黄继鹏. 红外弱小目标的分割预检测[J]. 光学精密工程, 2012,20(1): 171-178

JIN Yong-liang, WANG Yan-jie, LIU Yan-ying, HUANG Ji-peng. Pre-detection method for small infrared target[J]. Editorial Office of Optics and Precision Engineering, 2012,20(1): 171-178
靳永亮, 王延杰, 刘艳滢, 黄继鹏. 红外弱小目标的分割预检测[J]. 光学精密工程, 2012,20(1): 171-178 DOI： 10.3788/OPE.20122001.0171.

JIN Yong-liang, WANG Yan-jie, LIU Yan-ying, HUANG Ji-peng. Pre-detection method for small infrared target[J]. Editorial Office of Optics and Precision Engineering, 2012,20(1): 171-178 DOI： 10.3788/OPE.20122001.0171.

摘要

提出了一种目标分割预检测方法来提高检测红外弱小目标的准确性和实时性。针对红外图像的特点

利用改进的自适应背景感知算法抑制目标图像的背景以提高目标检测概率;根据已有的先验知识构造属性集

把灰度直方图限定在感兴趣区域

减少背景的影响;然后

利用属性直方图的最大熵进行图像分割以检测目标。为了提高分割算法运算速度

应用了快速递推算法。实验结果表明

本文提出的背景抑制算法能更好地抑制背景

提高图像的整体信噪比;分割算法具有更好的分割检测效果

候选目标点分割准确、虚警目标点较少

运算速度提高了91%。对分割图像进行后续处理

剔除了大部分虚警目标点

为后续目标准确检测提供了有力保障。

Abstract

A segmentation and detection method for small infrared targets is proposed to improve the accuracy of target detection. Aiming at the characters of an infrared image

an improved background perception algorithm is used to suppress backgrounds for increasing the target detection probability

and the bound set is constructed to limit the gray level histogram into a Region of Interest (ROI) to reduce the interference of background. Then

target detection is achieved through image segmentation using the maximum entropy of a 2D bound histogram. Furthermore

the fast recurring algorithm is applied to the proposed algorithm for accelerating the running speed of the segmentation algorithm. Experiment results show that proposed background suppression algorithm has the better performance in background suppression and can improve the signal to Noise Ratio (SNR) of the image. Moreover

the segmentation algorithm shows a better effectiveness in target segmentation and detection

and its candidate target is separated more accurate with less false alarm points and running speed has improved by 91%. Through post-process for the image

most of the false alarm points are eliminated

which provides powerful guarantee for the subsequent accurate detection.

关键词

Keywords

references

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