天基红外图像的点目标检测

孟祥龙; 张 伟; 丛明煜; 曹移明; 鲍文卓

doi:10.3788/OPE.20101809.2094

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天基红外图像的点目标检测

信息科学 | 更新时间：2020-08-12

- 天基红外图像的点目标检测
- Detection of point targets in space-based infrared images
- 光学精密工程 2010年18卷第9期页码：2094-2100
- 作者机构：
  
  哈尔滨工业大学空间光学工程研究中心,黑龙江哈尔滨,150001
- 作者简介：
- 基金信息：
  
  国家863高技术研究发展计划资助项目(No.2006AA1280)()
- DOI：10.3788/OPE.20101809.2094
  中图分类号： TP391;TP722.5
- 收稿日期：2010-06-27，
  
  修回日期：2010-07-27，
  
  网络出版日期：2010-09-29，
  
  纸质出版日期：2010-09-20
- 稿件说明：
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孟祥龙, 张伟, 丛明煜, 曹移明, 鲍文卓. 天基红外图像的点目标检测[J]. 光学精密工程, 2010,18(9): 2094-2100

MENG Xiang-long, ZHANG Wei, CONG Ming-yu, CAO Yi-ming, BAO Wen-zhuo. Detection of point targets in space-based infrared images[J]. 光学精密工程, 2010,18(9): 2094-2100
孟祥龙, 张伟, 丛明煜, 曹移明, 鲍文卓. 天基红外图像的点目标检测[J]. 光学精密工程, 2010,18(9): 2094-2100 DOI： 10.3788/OPE.20101809.2094.

MENG Xiang-long, ZHANG Wei, CONG Ming-yu, CAO Yi-ming, BAO Wen-zhuo. Detection of point targets in space-based infrared images[J]. 光学精密工程, 2010,18(9): 2094-2100 DOI： 10.3788/OPE.20101809.2094.

摘要

为了研究地球同步轨道卫星红外扫描相机图像星上处理技术

分析了美国国防支援计划(DSP)卫星Phase-Ⅱ阶段和改进后的星上信息处理机的基本处理流程

提出了一种适用于星上工作环境的红外扫描图像点目标检测双通道滤波方法。首先

采用均值滤波抑制背景

对背景去除后的残差图像进行自适应门限探测;在门限滤波的同时

采用峰值判别算法对峰值数据进行检波以降低自适应门限滤波产生的虚警;最后

采用融合算法对超过门限的图像及峰值检波图像的双通道数据进行目标确认。该算法在保证高目标检测率的同时降低了虚警率

简单可行且利于硬件实时实现。实验结果表明

当目标信噪比

6时

检测概率可达99.3%(虚警率为1.310

-3

);算法实时性分析表明

处理器主频为200 MHz时

算法处理能力为56.45 Mb/s

满足天基信息处理要求。

Abstract

In order to research the on-board data processing for infrared (IR) scan images in Geostationary Earth Orbit (GEO) satellite

processing flows of data processors in the Phase Ⅱ and DSP-Ⅰ satellites for U.S. Defense Support Program (DSP) are discussed. A point target detection algorithm for IR scan images is proposed based on a two-channel filter to suit for space conditions. Firstly

the background prediction is modeled by a mean filter to suppress background clutters

and the adaptive threshold is determined on the residual image after the background elimination. Then

the peak detection is used to detect the peaks in IR images to reduce probability of false alarm originating from the adaptive threshold. Finally

the target identification algorithm using fusion technique is performed for the data from two channels. Experiments show that the proposed algorithm can get high detection probability and low false-alarm probability

and is easy and convenient for real-time operation. The obtained results indicate that the detection probability reaches 99.3% (the false alarm probability is 1.310

-3

) when the input Signal-to-Noise ratio (SNR) is no less than 6. The real-time analysis of the algorithm shows that the data processing capability can achieve 56.45 Mb/s. The proposed algorithm can meet the need of space-based data processing.

关键词

Keywords

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