基于Contourlet及目标特性分析的弱小红外目标检测
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摘要
研究了一种复杂背景下红外小目标检测的新方法。根据远距离红外弱小目标在相平面上成像的各向同性特征以及目标与背景边缘分离困难的现状,提出了一种基于Contourlet及目标特性分析的弱小红外目标检测算法。首先采用Contourlet变换对图像中的低频起伏背景及边缘与随机噪声和目标进行分离;然后对红外目标进行基于各向同性特征的目标提取;最后对目标进行分割、检测以及定位,并输出目标信息。通过与一些传统方法进行基于主观视觉和客观指标的对比发现,该算法可有效分离目标与低频背景、随机噪声及背景边缘,对红外图像基于弱小目标检测背景处理时,效果较好。
A new method of small infrared target detection under complex background is studied in this paper. The imaging of long-range infrared dim and small targets on phase plane has isotropic characteristics. Separating target from background edge is very difficult. Then, a dim and small infrared target detection algorithm based on Contourlet and target characteristic analysis is proposed. First, the contourlet transform is used to separate the low-frequency fluctuating background and edge from the random noise and target. Then the infrared target is extracted based on isotropic feature. Finally, the target is segmented, detected and positioned, and the target information is output. By comparing with some traditional methods and methods proposed in literature based on subjective vision and objective indicators, the results show that the algorithm can effectively separate the target from low-frequency background, random noise and background edges, and has a better effect in infrared image background detection based on small and dim targets.
A new method of small infrared target detection under complex background is studied in this paper. The imaging of long-range infrared dim and small targets on phase plane has isotropic characteristics. Separating target from background edge is very difficult. Then, a dim and small infrared target detection algorithm based on Contourlet and target characteristic analysis is proposed. First, the contourlet transform is used to separate the low-frequency fluctuating background and edge from the random noise and target. Then the infrared target is extracted based on isotropic feature. Finally, the target is segmented, detected and positioned, and the target information is output. By comparing with some traditional methods and methods proposed in literature based on subjective vision and objective indicators, the results show that the algorithm can effectively separate the target from low-frequency background, random noise and background edges, and has a better effect in infrared image background detection based on small and dim targets.
引文
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[13] 张智丰,裴志利,张亚荣.加权融合特征耦合Top-Hat变换的红外目标检测算法[J].计算机工程与设计,2017,38(10):2838-2844.ZHANG ZH F,PEI ZH L,ZHANG Y R.Infrared target detection algorithm based on Top-Hat transform and multi-feature weighted fusion feature[J].Computer Engineering and Design,2017,38(10):2838-2844.
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[15] 李静,刘兴淼,薛福来.基于循环平移Contourlet变换的红外小目标检测方法[J].红外,2013,34(2):39-43.LI J,LIU X M,XUE F L.Small infrared object detection method based on cycle spinning contourlet transform[J].Infrared,2013,34(2):39-43.
[16] 刘兴淼,王仕成,赵静,等.基于非下采样Contourlet变换的红外小目标检测方法[J].红外,2011,32(1):35-40.LIU X M,WANG SH CH,SHAO J,et al.Small infrared target detection based on nonsubsampled contourlet transform[J].Infrared,2011,32(1):35-40.
[17] 郭冰涛,王晓蕊,王小兵,等.诱饵弹作用后导引头成像特征建模及跟踪性能分析[J].红外与激光工程,2015,44(7):2027-2033.GUO B T,WANG X R,WANG X B,et al.Analysis of imaging features and tracking performance of seeker after decoys jamming[J].Infrared and Laser Engineering,2015,44(7):2027-2033.
[18] 刘可辉,王晓蕊,张卫国.红外点目标成像信噪比建模分析[J].红外与激光工程,2014,43(7):2143-2147.LIU K H,WANG X R,ZHANG W G.Modeling and analysis on SNR of infrared point target[J].Infrared and Laser Engineering,2014,43(7):2143-2147.
[19] 刘润邦,朱志宇.基于视觉对比机制的红外弱小目标检测方法[J].激光与红外,2017,47(9):1169-1173.LIU R B,ZHU ZH Y.Infrared dim target detection based on visual contrast mechanism[J].Laser & Infrared,2017,47(9):1169-1173.
[20] 温佩芝,史泽林,于海斌.基于小波变换的复杂海面背景红外小目标检测[J].激光与红外,2003,33(6):449-452.WEN P ZH,SHI Z L,YU H B.Wavelet transform based detection for small IR target in complex sea background[J].Laser & Infrared,2003,33(6):449-452.
[2] 王志,陈平,潘晋孝.基于深度学习的复杂背景下目标检测[J].重庆理工大学学报(自然科学),2018,32(4):171-176.WANG ZH,CHEN P,PAN J X.Object detection based on deep learning in complex background[J].Journal of Chongqing University of Technology(Natural Science),2018,32(4):171-176.
[3] 王忍宝,许四祥,李天甲,等.基于DSP/BIOS图像处理的弱小目标检测[J].红外技术,2017,39(6):500-504.WANG R B,XU S X,LI T J,et al.Detection of weak and small targets based on DSP/BIOS image processing[J].Infrared Technology,2017,39(6):500-504.
[4] 葛鹏,崔国龙,孔令讲,等.高速弱小目标检测的并行处理方法与性能分析[J].信号处理,2017,33(2):127-134.GE P,CUI G L,KONG L J,et al.Parallel processing technique for high speed small target detection and performance analysis[J].Journal of Signal Processing,2017,33(2):127-134.
[5] 易翔,王炳健.基于多特征的快速红外弱小目标检测算法[J].光子学报.2017,46(6):610001-610002.YI X,WANG B J.Fast infrared and dim target detection algorithm based on multi-feature[J].Acta Photonica Sinica,2017,46(6):610001-610002.
[6] 张祥越,丁庆海,罗海波,等.基于改进LCM的红外小目标检测算法[J].红外与激光工程,2017,46(7):726001-726002.ZHANG X Y,DING Q H,LUO H B,et al.Infrared dim target detection algorithm based on improved LCM[J].Infrared and Laser Engineering.2017,46(7):726001-726002.
[7] 姚成乾,陈伟.基于改进粒子算法的红外弱小目标检测研究[J].激光与光电子学进展,2017,54(11):143-148.YAO CH Q,CHEN W.Infrared dim target detection based on improved particle swarm optimization algorithm[J].Laser & Optoelectronics Progress,2017,54(11):143-148.
[8] 周苑,张健民,林晓.基于加权LoG算子的红外弱小目标检测方法研究[J].应用光学,2017,38(1):114-119.ZHOU Y,ZHANG J M,LIN X.Infrared small target detection using weighting LoG operator[J].Journal of Applied Optics,2017,38(1):114-119.
[9] 刘昆,刘卫东.基于加权融合特征与Ostu分割的红外弱小目标检测算法[J].计算机工程,2017,43(7):253-260.LIU K,LIU W D.Detection algorithm for infrared dim small targets based on weighted fusion feature and ostu segmentation[J].Computer Engineering,2017,43(7):253-260.
[10] 陈玉文,李玲,辛云宏.基于视觉对比度机制的红外小目标检测[J].激光与红外,2017,47(2):252-256.CHEN Y W,LI L,XIN Y H.Infrared small target detection based on visual contrast mechanism[J].Laser & Infrared,2017,47(2):252-256.
[11] 李思俭,樊祥,朱斌,等.基于运动模糊复原技术的红外弱小目标检测方法[J].光学学报,2017,37(6):65-71.LI S J,FAN X,ZHU B,et al.A method for small infrared targets detection based on the technology of motion blur recovery[J].Acta Optica Sinica,2017,37(6):65-71.
[12] 熊斌,黄心汉,王敏.基于自适应目标图像恢复的红外弱小目标检测[J].华中科技大学学报(自然科学版),2017,45(10):25-30.XIONG B,HUANG X H,WANG M.Infrared dim small target detection based on adaptive target image recovery[J].Journal of Huazhong University of Science and Technology (Natural Science Edition),2017,45(10):25-30.
[13] 张智丰,裴志利,张亚荣.加权融合特征耦合Top-Hat变换的红外目标检测算法[J].计算机工程与设计,2017,38(10):2838-2844.ZHANG ZH F,PEI ZH L,ZHANG Y R.Infrared target detection algorithm based on Top-Hat transform and multi-feature weighted fusion feature[J].Computer Engineering and Design,2017,38(10):2838-2844.
[14] 尹丹艳.基于Contourlet和SVR的红外弱小目标检测方法[J].科技广场,2017(189):26-29.YIN D Y.Detection of small infrared target based on contourlet and SVR[J].Science Mosaic,2017(189):26-29.
[15] 李静,刘兴淼,薛福来.基于循环平移Contourlet变换的红外小目标检测方法[J].红外,2013,34(2):39-43.LI J,LIU X M,XUE F L.Small infrared object detection method based on cycle spinning contourlet transform[J].Infrared,2013,34(2):39-43.
[16] 刘兴淼,王仕成,赵静,等.基于非下采样Contourlet变换的红外小目标检测方法[J].红外,2011,32(1):35-40.LIU X M,WANG SH CH,SHAO J,et al.Small infrared target detection based on nonsubsampled contourlet transform[J].Infrared,2011,32(1):35-40.
[17] 郭冰涛,王晓蕊,王小兵,等.诱饵弹作用后导引头成像特征建模及跟踪性能分析[J].红外与激光工程,2015,44(7):2027-2033.GUO B T,WANG X R,WANG X B,et al.Analysis of imaging features and tracking performance of seeker after decoys jamming[J].Infrared and Laser Engineering,2015,44(7):2027-2033.
[18] 刘可辉,王晓蕊,张卫国.红外点目标成像信噪比建模分析[J].红外与激光工程,2014,43(7):2143-2147.LIU K H,WANG X R,ZHANG W G.Modeling and analysis on SNR of infrared point target[J].Infrared and Laser Engineering,2014,43(7):2143-2147.
[19] 刘润邦,朱志宇.基于视觉对比机制的红外弱小目标检测方法[J].激光与红外,2017,47(9):1169-1173.LIU R B,ZHU ZH Y.Infrared dim target detection based on visual contrast mechanism[J].Laser & Infrared,2017,47(9):1169-1173.
[20] 温佩芝,史泽林,于海斌.基于小波变换的复杂海面背景红外小目标检测[J].激光与红外,2003,33(6):449-452.WEN P ZH,SHI Z L,YU H B.Wavelet transform based detection for small IR target in complex sea background[J].Laser & Infrared,2003,33(6):449-452.