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强噪声背景红外微弱动目标集成检测 被引量:4

Integration detection algorithm of infrared small dim moving target based on strong complex noise
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摘要 微弱运动目标检测一直是红外成像识别、跟踪领域中的重要课题。我们提出了一种新的基于强复杂噪声背景的红外微弱运动目标集成检测算法。针对复杂噪声,提出一种新的基于邻域梯度累积平方误差最小原则的自适应滤波算法。该算法,对各种加性、乘性噪声的滤波性能优异且均衡,适合对复杂噪声进行滤波。针对微小目标检测,我们提出一种基于运动平台的微小目标运动场集成检测算法。该算法,改变传统微小目标检测算法,要求提前对运动背景进行精确全域运动估计及补偿的模式,而只对图像运动场进行估计及补偿,提高了算法的可实现性。 Detection of small dim moving target is the important task in infrared image recognition and tracking. A new adapt filtering algorithm based on minimum cumulation-squared error (MCSE) of gradients in neighborhood is proposed for infrared small dim moving target in strong complex noise entironment. The performance of the algorithm is good and balanced for various plus noise, multiplicative noise, or strong complex noise. For detecting small objects, an integration detection algorithm of small moving target on moving camera is presented. The traditional detection algorithms need accurate global motion estimation and compensation, and the new algorithm only processes motion field and its application field is improved.
出处 《电波科学学报》 EI CSCD 北大核心 2008年第3期438-442,共5页 Chinese Journal of Radio Science
基金 国家高科技发展计划(2004AA823120) 国家自然科学基金(10376005)资助项目
关键词 强噪声 复杂噪声 微弱目标 运动检测 strong noise complex noise small dim target moving detection
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  • 1杨文,陈嘉宇,孙洪,徐新.基于SAR图像的点状目标检测方法研究[J].电波科学学报,2004,19(3):362-366. 被引量:14
  • 2[1]T D Ross, J J Bradley, L J Hudson, et al.. SAR ATR-So what′s the problem? -an MSTAR perspective, 1999, sPIEls 13th Annual International Symposium on AeroSense, Algorithms for SAR Imagery VI,Paper 3721~67 被引量:1
  • 3[2]L M Novak,G J Owirka, W S. Brower. Performance of 10-and 20-Target MSE Classfiers[J]. IEEE Trans.on Aerospace and Electronic Systems. 2000, 36 (4):1279~1289. 被引量:1
  • 4[4]A Lopes, E Nezry, R Touzi,et al.. Structure detection and statistical adaptive speckle filtering in SAR images[J]. International Journal of Remote Sensing,1993, 14(9): 1735~1758. 被引量:1
  • 5[5]L M Novak, G J Owirka, and C M Netishen. Performance of a high-resolution polarimetric SAR automatic target recognition system[J]. Lincoln Laboratory Journal, 1993, 6 (1): 11~23. 被引量:1
  • 6[6]C Oliver, S Quegan. Understanding synthetic aperture radar Images[M]. Artech House Inc., 685 Canton Street, Norwood, MA02062, 1998. 被引量:1
  • 7[7]L M Kaplan. Improved synthetic aperture radar target detection via extended fractal features [J ]. IEEE Trans. on Aerospace and Electronic Systems, 2001,37(2): 436~451. 被引量:1
  • 8[8]M J Shensa. The discrete wavelet transform: wedding the d trous and mallat algorithms[J]. IEEE Trans. On Signal Processing, 1992, 45(10): 2464~2482. 被引量:1
  • 9张澄波,综合孔径雷达原理、系统分析与应用,1989年 被引量:1
  • 10Li Jian,IEEE Trans Aerosp Electron Syst,1996年,32卷,2期,613页 被引量:1

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