基于邻域特征的红外低慢小目标检测

详细信息    查看全文 | 推荐本文 |

英文篇名：Infrared low, slow and small target detection based on neighborhood characteristics 作者：南天章 ; 耿建君 ; 陈旭 ; 陈颖 英文作者：Nan Tianzhang;Geng Jianjun;Chen Xu;Chen Ying;Tianjin Jinhang Institute of Technical Physics;Beijing Institute of Electronic Engineering;Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences; 关键词：图像处理 ; 目标检测 ; 红外搜索系统 ; 低慢小目标 英文关键词：image processing;;target detection;;infrared search system;;low,slow and small target 中文刊名：HWYJ 英文刊名：Infrared and Laser Engineering 机构：天津津航技术物理研究所;北京电子工程总体研究所;中国科学院天津工业生物技术研究所; 出版日期：2019-04-25 出版单位：红外与激光工程 年：2019 期：v.48 语种：中文; 页：HWYJ2019S1026 页数：7 CN：S1 ISSN：12-1261/TN 分类号：180-186

摘要

红外搜索系统具有不发射电磁波、抗电磁干扰能力强、目标指示精度高等优势,在低慢小目标探测领域有很好的应用前景。目前国内外基于红外搜索系统的目标检测算法通常利用当前图像与背景图像配准、差分的手段提取疑似目标,往往需要较大的存储空间保存周视背景图像,高精度实时图像配准算法的工程化应用也有较大难度。针对以上问题,设计了一种基于邻域特征的红外低慢小目标检测方法。通过高通滤波、边缘检测法提取疑似目标、目标邻域特征值统计法剔除背景干扰、多帧图像目标信息相关等处理过程,可在有效排除地物、云层及飞鸟等多种干扰的同时,准确地检测图像中的无人机目标。试验结果表明,该方法相比传统LCM算法目标检测概率更高、虚警率更低,且不涉及图像差分,具有对硬件资源要求低、实时性好等优点,有较高的工程应用价值。
        The infrared search system has the advantages of not emitting electromagnetic wave, strong anti-electromagnetic interference ability and high precision of target indication, and has a good application prospect in the field of low, slow and small target detection. At present at home and abroad, the target detection algorithm of infrared search system usually extracts the suspected target by using the current image and the background image registration and difference, which is often necessary to save the panoramic background images in the large storage space, and the engineering application of high precision real-time image registration algorithm is also difficult. For the above questions, a infrared low,slow and small target detection method was designed for the infrared search system. Through the processes of morphological filtering, extracting suspected targets with edge detection method, eliminating background interference with target neighborhood eigenvalue statistical method and correlating targetinformation based on multi-frame image, it can effectively eliminate the interference of ground objects,clouds and birds, while accurately detecting the UAV′ s target in the image. Experimental results show that this method has higher target detection probability and lower false alarm rate than the traditional LCM algorithm. Moreover, it does not involve image difference, and has the advantages of low demand for hardware resources and good real-time performance, etc., and has high engineering application value.

引文

[1]Shen Yang,Tang Mingwen.Overview of airborne infrared search and tracking system(IRST)[J].Infrared Technology,2003,25(1):13-18.(in Chinese)申洋,唐明文.机载红外搜索跟踪系统(IRST)综述[J].红外技术,2003,25(1):13-18.
    [2]Zhu Zhenping.Research on the target detection technology of peripheral infrared search system[D].Changsha:University of National Defense Science and Technology,2011:29-30.(in Chinese)朱振平.周视红外搜索系统目标检测技术研究[D].长沙:国防科学技术大学,2011:29-30.
    [3]Qi S,Ma J,Tao C,et al.A robust directional saliency-based method for infrared small-target detection under various complex backgrounds[J].IEEE Geoscience and Remote Sensing Letters,2013,10(3):495-499.
    [4]Chen C L P,Li H,Wei Y,et al.A local contrast method for small infrared target detection[J].IEEE Transactions on Geoscience and Remote Sensing,2014,52(1):574-581.
    [5]Zhang Xiangyue,Ding Qinghai,Luo Haibo,et al.Infrared small target detection algorithm based on improved LCM[J].Infrared and Laser Engineering,2017,46(7):0726002.(in Chinese)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):0726002.
    [6]Zeng Ming,Li Jianxun.Infrared dim target detection method based on adaptive morphological Top-Hat filter[J].Journal of Shanghai Jiaotong University,2006,40(1):90-93.(in Chinese)曾明,李建勋.基于自适应形态学Top-Hat滤波器的红外弱小目标检测方法[J].上海交通大学学报,2006,40(1):90-93.
    [7]Wang X,Lv G,Xu L.Infrared dim target detection based on visual attention[J].Infrared Physics&Technoolgy,2012,55(6):513-521.
    [8]Frank Y Shih,Wu Yita.Decomposition of arbitrary grayscale morphological structuring elements[J].Pattern Recognition,2005,38(12):2323-2332.
    [9]Wang Kang.A detection algorithm for infrared dim target in complicated sea-sky background[J].Optical and Optoelectronic Technology,2016,14(3):2-3.(in Chinese)王康.一种复杂海天背景下红外弱小目标检测算法[J].光学与光电子技术,2016,14(3):2-3.
    [10]Wang Peizao,Wang Weihua,Wang Haisong,et al.Infrared target detection based on the multi-level synthesis classifier[J].Software Engineering,2017,20(12):4-6.(in Chinese)王培早,王卫华,王海松,等.基于多级综合分类器的红外目标检测[J].软件工程,2017,20(12):4-6.