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基于数学形态学的红外小目标跟踪研究 被引量:12

The Analysis of Infrared Small Target Tracking Based on Mathematical Morphology
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摘要 为了提高红外小目标跟踪算法的性能和实用性,根据红外小目标的特性,选用数学形态学方法先对目标进行波门检测,依据检测结果来实现对目标的跟踪。在具体计算时,提出了一种新的形态学算子使膨胀运算和阈值分割合为一步,节约了计算时间。考虑到波门内可能出现虚警或漏警的情况,提出了有效的解决方法。最后通过实际拍摄的不同情况下的红外图像,进行了红外小目标的跟踪实验,实验结果表明了算法在实时性和准确性上都达到了很好的效果。 In order to improve performance and practicability of infrared small target tracking algorithm,based on the traits of IR small target,the mathematical morphology was adopted for detection in the target area,and target tracking was realized based on the results.In exact calculation,a new method that combining dilation operation and threshold segmentation was presented,and the time was reduced.Considering false alarm and false dismissal,effective solution was discussed here.The IR small target tracking experiments were done by real IR images taken in different situations,and the results demonstrate that the algorithms have good performance in real-time demand and veracity.
出处 《弹箭与制导学报》 CSCD 北大核心 2012年第2期15-18,共4页 Journal of Projectiles,Rockets,Missiles and Guidance
关键词 红外小目标跟踪 波门跟踪 数学形态学 infrared small target tracking gate tracking mathematical morphology
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  • 1向桂英,艾斯卡尔.艾木都拉,于伟俊,地里木拉提.吐尔逊.基于粒子滤波和数据关联的多目标跟踪算法[J].光电子.激光,2009,20(2):244-247. 被引量:9
  • 2王兵学,张启衡,王敬儒,魏国.凝视型红外搜索跟踪系统作用距离模型中参数值的确定[J].红外技术,2004,26(4):6-10. 被引量:20
  • 3宗思光,王江安,陈启水.海空复杂背景下红外弱点目标检测新算法[J].光电工程,2005,32(4):9-12. 被引量:20
  • 4赵举廉,褚云汉,赵进豪,李茜,顾里平,杨俊霞.远距离热成像系统的光谱匹配因数[J].红外技术,1996,18(1):16-18. 被引量:3
  • 5Jackway P T. Improved morphological Top-hat [J]. Electronics Letters, 2000, 36(14) : 1194-1195.
  • 6Soni T, Zeidler J R, Ku W H. Performance evaluation of 2-D adaptive prediction filters for detection of small objects in image data [J]. IEEE Transaction on Image Processing, 1993, 2 (3): 327-340.
  • 7Deshpande S D, Er M H, Ronda V, et al. Maxmean and max-median filters for detection of smalltargets[C]//Proceedings of SPIE. Bellingham,WA, USA:SPIE, 1999, 3809: 74-83.
  • 8Serra J. Image analysis and mathematical morphology [M]. New York: Academic Press, 1982.
  • 9Andrei C J, Michael W, Jos R. Morphological hattransformation scale spaces and their use in pattern classification [J]. Pattern Recognition, 2004, 37: 901-915.
  • 10De I, Chanda B, Chattopadhyay B. Enhancing effective depth-of-field by image fusion using mathematical morphology [J]. Image and Vision Computing, 2006, 24: 1278-1287.

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