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双目遥感凝视系统中运动小目标的快速自动检测
引用本文:屈有山,樊学武,李英才,汶德胜,田维坚.双目遥感凝视系统中运动小目标的快速自动检测[J].光学技术,2005,31(6):811-813.
作者姓名:屈有山  樊学武  李英才  汶德胜  田维坚
作者单位:中国科学院西安光学精密机械研究所,陕西,西安,710068;中国科学院西安光学精密机械研究所,陕西,西安,710068;中国科学院研究生院,北京,100039
基金项目:国家863高技术资助项目
摘    要:从双目遥感凝视系统的视场重叠区进入系统的信息量大于通过非重叠区的信息量,根据这一特征建立了一种新的运动小目标双目并行快速实时自动检测算法。首先采用差分向量无穷范数算法对原始图像序列做预处理,去掉大量低频噪音和背景,然后采用光流场法对运动小目标进行分割,最后用所提出的空间时间并行快速判定算法对分割的可疑运动小目标进行判定。实验结果表明:由于识别判定算法的空间时间是并行处理的,所以识别判定的平均速度比单目视觉系统提高了50%;在图像信噪比不小于5dB的情况下,准确判定识别的概率为97%。

关 键 词:运动小目标  遥感  检测  光流场  凝视  识别
文章编号:1002-1582(2005)06-0811-03
修稿时间:2005年1月22日

High-speed auto-detection of moving small targets in remote sensing staring binocular imaging system
QU You-shan,FAN Xue-wu,LI Ying-cai,WEN De-sheng,TIAN Wei-jian.High-speed auto-detection of moving small targets in remote sensing staring binocular imaging system[J].Optical Technique,2005,31(6):811-813.
Authors:QU You-shan  FAN Xue-wu  LI Ying-cai  WEN De-sheng  TIAN Wei-jian
Institution:QU You-shan~1,FAN Xue-wu~1,LI Ying-cai~
Abstract:According to the feature of remote sensing staring binocular imaging system,the information quantity passed through the overlapped field of view is larger than that passed through the non-overlapped field of view,a new parallel high-speed automatic detecting algorithm of moving small targets is established.The algorithm firstly used the Infinite Norms of the difference vectors of the processed images as a preprocessing algorithm to get rid of most of low frequency noise points and background,then used Optic Flow to segment the moving small targets,and finally used the novel space-time parallel high-speed determining method proposed to determine whether the doubtful moving small target was a true target or not.The experiments results prove that the average determining speed of the space-time parallel processing determining method is improved 50% than that of the monocular imaging system,in the SNR of processed images is no less than 5 dB,the correct determining probability is 97%.
Keywords:moving small targets  remote sensing  detection  optic flow  recognition
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