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复杂背景下红外点目标的检测 被引量:29

Detection of infrared point target filters in varying clutter
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摘要 在分析红外点目标、噪声及杂波模型的基础上 ,提出了基于二次滤波的复杂背景下红外点目标的检测算法 ,该算法由二阶滤波器组成。根据点目标的模型特点 ,通过选择合适的高通滤波器 ,可有效地增强信噪比、抑制噪声。实验结果表明该算法效果良好。 In this paper, an infrared point target detection algorithm based on two filters in spatially varying clutter is presented. The target and clutter model is analyzed correctly, and very small (point) target under spatially varying clutter background is successfully detected with the algorithm, when the target and clutter are both moving across the image scene. This method can reduce the cost of computation, track the target in real-time, enhance the SNR, and suppress the clutter effectively. \;
出处 《红外与激光工程》 EI CSCD 北大核心 2001年第2期96-98,111,共4页 Infrared and Laser Engineering
关键词 复杂背景 马尔可夫模型 高通滤波 自适应门限 红外检测 高目标检测 Point target Markov model High-pass filtering Adaptive threshold Segmentation
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参考文献6

  • 1[1]Charlene E Caefer, Jerry Siliverman. Optimization of point target tracking filters[J]. IEEE transactions on aerospace and electronic systems, 2000, 36(1): 15~25.
  • 2[2]Alexis P Tzannes. Dana H Brooks. Detection of point targets in image sequences by hypothesis testing a temporal test first approach[A]. IEEE, 1999. 3377~3380.
  • 3[3]Warren R C. The real time calculation of cloud motion in infrared image sequences using mathematics morphology operations[A]. IEEE, 1999. 83~89.
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