[1]袁静珍,金 旺.基于改进双边滤波的多尺度运动目标检测方法[J].红外技术,2019,41(8):772-777.[doi:10.11846/j.issn.1001_8891.2019080013]
 YUAN Jingzhen,JIN Wang.Multi-scale Moving Target Detection Method Based on Improved Bilateral Filtering [J].Infrared Technology,2019,41(8):772-777.[doi:10.11846/j.issn.1001_8891.2019080013]
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基于改进双边滤波的多尺度运动目标检测方法
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《红外技术》[ISSN:1001-8891/CN:CN 53-1053/TN]

卷:
41卷
期数:
2019年第8期
页码:
772-777
栏目:
出版日期:
2019-08-21

文章信息/Info

Title:
Multi-scale Moving Target Detection Method Based on
Improved Bilateral Filtering
文章编号:
1001-8891(2019)08-0772-06
作者:
袁静珍1金 旺2
1. 韩山师范学院 物理与电子工程学院,广东 潮州 521041;2. 北京邮电大学 电子工程学院,北京 100876
Author(s):
YUAN Jingzhen1JIN Wang2
1. Department of Physics and Electronic Engineering, Hanshan Normal University, Chaozhou 521041, China;
2. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
关键词:
改进双边滤波三维匹配滤波多尺度检测弱小目标检测NNLoG算子
Keywords:
improved bilateral filtering 3D matching filtering multi-scale detection dim target detection NNLoG operator
分类号:
TP391
DOI:
10.11846/j.issn.1001_8891.2019080013
文献标志码:
A
摘要:
提出一种基于改进双边滤波的运动多尺度目标检测方法,以提高对弱小目标的检测能力。首先对视频或序列红外图像进行改进双边滤波处理,提高目标的对比度,同时抑制背景的边缘噪声及随机噪声。然后对目标进行三维匹配滤波,获得若干组速度匹配叠加强度图像。最后,在这些图像中进行基于NNLoG(归一化负LoG算子)的多尺度目标检测,得到序列图像或视频段的最佳匹配速度及增强后的图像。可最终计算出目标在序列图像或视频中的运动方程。通过大量的实验及对比实验可知,改进双边滤波、三维匹配滤波及NNLoG算子综合处理效果都较好,可有效检测序列图像或视频中的目标。
Abstract:
 A multi-scale moving target detection method based on improved bilateral filtering is proposed to enhance the detection ability in the case of dim and small targets. First, a video or sequence of infrared images are processed by an enhanced bilateral filtering to improve the contrast of the target, while suppressing the background edge noise and random noise. Subsequently, three-dimensional matched filtering is performed and several sets of velocity matching superimposed intensity images are obtained. Finally, multi-scale target detection based on normalized negative LoG operator (NNLoG) is conducted for the obtained images to realize the best matching speeds and enhanced images. The equation of motion of a target in a sequential image or video is finally calculated. Numerous experiments and comparisons show that the improved bilateral filtering, three-dimensional matched filtering and NNLoG operator when integrated for processing yield superior results and can effectively detect the target image in the sequence or video.

参考文献/References:

[1] 李天甲, 许四祥, 姚志生, 等. 基于DSP的两帧差分和改进半因果弱小目标检测[J]. 激光与红外, 2017, 47(10): 1316-1320.
LI Tianjia, XU Sixiang, YAO Zhisheng, et al. Dim and small target detection based on two frame difference and modified semi-causal with DSP[J]. Laser & Infrared, 2017, 47(10): 1316-1320.
[2] 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 Renbao, XU Sixiang, LI Tianjia, et al. Detection of weak and small targets based on DSP/BIOS image processing[J]. Infrared Technology, 2017, 39(6): 500-504.
[3] 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 Xiangyue, DING Qinghai, LUO Haibo, et al. Infrared dim target detection algorithm based on improved LCM[J]. Infrared and Laser Engineering, 2017, 46(7): 726001-726002.
[4] 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: 111101.
YAO Chengqian, CHEN Wei. Infrared dim target detection based on improved particle swarm optimization algorithm[J]. Laser & Optoelectronics Progress, 2017, 54: 111101.
[5] 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 Yuan, ZHANG Jianmin, LIN Xiao. Infrared small target detection using weighting LoG operator[J]. Journal of Applied Optics, 2017, 38(1): 114-119.
[6] 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 Kun, LIU Weidong. Detection algorithm for infrared dim small targets based on weighted fusion feature and Ostu segmentation[J]. Computer Engineering, 2017, 43(7): 253-260.
[7] 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 Yuwen, LI Lin, XIN Yunhong. Infrared small target detection based on visual contrast mechanism[J]. Laser & Infrared, 2017, 47(2): 252-256.
[8] 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 Renbang, ZHU Zhiyu. Infrared dim target detection based on visual contrast mechanism[J]. Laser & Infrared, 2017, 47(9): 1169-1173.
[9] 邓剑勋, 熊忠阳, 邓欣. 基于信息融合的空中弱小目标检测[J]. 电光与控制, 2018, 25(2): 5-10.
DENG Jianxun, XIONG Zhongyang, DENG Xin. Dim target detection in air based on information fusion[J]. Electronics Optics & Control, 2018, 25(2): 5-10.
[10] 蒲静松, 许东, 刘乙君, 等. 星空背景下红外弱小目标的快速检测[J]. 激光与红外, 2017, 47(4): 513-518.
PU Jinsong, XU Dong, LIU Yijun, et al. Rapid detection of infrared dim targets under starry sky background[J]. Laser & Infrared, 2017, 47(4): 513-518.
[11] 孙慧婷, 姜志, 王军, 等. 一种改进的红外弱小目标快速检测方法[J]. 激光与红外, 2017, 47(10): 1310-1315.
SUN Huiting, JIANG Zhi, WANG Jun, et al. An improved detection method for infrared dim and small target[J]. Laser & Infrared, 2017, 47(10): 1310-1315.
[12] 孙皓泽, 常天庆, 王全东, 等. 一种基于分层多尺度卷积特征提取的坦克装甲目标图像检测方法[J]. 兵工学报, 2017, 38(9): 1681-1691.
SUN Haoze, CHANG Tianqing, WANG Quandong, et al. Image detection method for tank and armored targets based on hierarchical nulti-scale convolution feature extraction[J]. Armamentarii, Acta. 2017, 38(9): 1681-1691.
[13] 袁耀东, 许红艳, 陶琳. 一种新颖的强海杂波背景下弱小目标鲁棒检测算法[J]. 红外技术, 2017, 39(11): 1054-1059.
YUAN Yaodong, XU Hongyan, TAO Ling. A novel infrared small-dim object detection under complex sea-clutter background[J]. Infrared Technology, 2017, 39(11): 1054-1059.
[14] ZHENG H, LIU J, GAO J, et al. Feature detection method for small targets of complex multimedia images in cloud environment[J]. Multimed Tools Appl. 2017, 76: 17095-17112.
[15] Razakarivony S, Jurie F. A novel target detection algorithm combining foreground and background manifold-based models[J]. Machine Vision and Applications, 2016, 27: 363-375.
[16] 秦剑, 陈钱, 钱惟贤. 基于光流估计和自适应背景抑制的弱小目标检测[J]. 光子学报, 2011, 40(3): 476-481.
QIN Jian, CHEN Qian, QIAN Weixian. A detection algorithm for dim and small infrared target based on the optical flow estimation and the adaptive background suppression[J]. Acta Photonica Sinica, 2011, 40(3): 476-481.
[17] Reed I S, Gagliardi R M, SHAO H M. Application of three-dimensional filtering to moving target detection[J]. IEEE Transactions on Aerospace And Electronic Systems, 1983, 19(6): 898-905.
[18] Reed I, Gagliardi R, Stotts L. Optical moving target detection with 3-D matched filtering [J]. IEEE Transactions on Aerospace And Electronic Systems, 1988, 24(4): 327-336.
[19] 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 Xiang, WANG Binjian. Fast infrared and dim target detection algorithm based on multi-feature[J]. Acta Photonica Sinica, 2017, 46(6): 610001-610002.

相似文献/References:

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 SUN Shixin,ZHENG Zhiyun.Genetic Algorithm for Infrared Multi-target Detection Based on Multi-scale NNLoG Feature[J].Infrared Technology,2019,41(8):837.[doi:10.11846/j.issn.1001_8891.201909007]

备注/Memo

备注/Memo:
收稿日期:2019-02-15;修订日期:2019-04-17.
作者简介:袁静珍(1975-),女,广东揭阳人,硕士,副教授,研究方向:电子通信与信号处理技术、计算机应用技术。E-mail:zengeiruo4@163.com。
基金项目:北京市自然科学基金(1163031),广东省教育部产学研结合项目(2012B091100288)。
更新日期/Last Update: 2019-08-20