用户名: 密码: 验证码:
基于红外序列图像的地物类型反演、目标检测与被动测距研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
随着红外传感器技术的发展,凝视红外探测系统在军事领域中的应用越来越广。相对于空中和海面而言,凝视红外探测系统在地面应用难度更大,其主要难点有:(1)目标及地物背景种类繁多;(2)目标易被复杂背景淹没或遮挡;(3)探测平台相对运动;(4)成像条件影响检测性能;(5)被动系统难以测距等。针对上述难点,本文开展了地物类型反演、地面复杂背景下红外目标检测以及被动测距究等工作,主要研究成果如下:
     1.构建了单层热能交换模型,仿真分析了典型地物的辐射统计特性,利用外场实测数据验证了模型的准确性;基于单层热能交换模型建立了相应地物表面的热平衡函数,利用相对稳定的地物光电特性参数以假设检验方式进行类型反演。
     2.对块匹配方法进行改进,实现了地面运动背景的快速补偿;针对单波段红外探测系统,基于图像理解的思想提出基于感兴趣区域的地面弱小运动目标检测算法;针对双波段红外探测系统,提出基于差分图像融合的地面弱小目标检测算法,结合了差分算法的时域优势和多传感器处理的空域优势,两种算法均有效提高了弱小运动目标的检测性能。
     3.提出一种基于改进的圆投影向量的图像匹配算法,不仅实现了运动背景的快速补偿,还可以构建面目标描述模型。在此基础上,针对运动面目标易出现的遮挡、目标机动等问题,提出一种基于圆投影向量和粒子滤波的地面运动面目标检测与跟踪算法。另外,针对地面运动目标非合作的情况提出一种基于综合信息度量的的地面运动目标检测和跟踪算法,不仅保证了算法有效性,还对地面运动小目标和面目标均具有通用性。
     4.分析了探测系统成像条件对图像像素灰度的影响,利用红外图像的灰度映射变换得到能够真实反映背景辐射量的表观温度图像;基于表观温度图像在像素邻域滑窗内提取相应特征集,采用假设检验方法检测静止目标,并针对不同成像条件提出了自适应滑窗的选择方法。
     5.构建了凝视红外成像系统的目标作用距离模型,证明了面/小目标与背景的辐射通量差具有相同表达形式,利用红外图像像素灰度与目标辐射通量之间的关系,推导了单站单波段与双波段条件下的被动测距方法。
     最后对凝视红外探测系统的组成、功能、研制及其外场试验等情况进行了总结。
With the development of infrared sensor technology, staring infrared detection systems are being applicated more and more widely in the military field. Compared with the air and sea applications, it is more difficult in terrestrial applications. And the main problems are shown as follows: (1) the types of the target and the typical ground are complicated, (2) the target is easy to be blocked or submerged, (3) the system platform is relative locomotory commonly, (4) the imaging condition affects the detection performance, (5) the passive ranging is difficult, etc.
     According to the abovementioned difficulties, the inversion of the typical ground, the target detection under complicated ground condition and the passive ranging are investigated in this thesis. And the main contributions are shown as follows:
     1. The uniform single-level heat-exchange model is put forward, and the statistics characteristic for the typical ground infrared radiance is emulated, whose veracity is verified by the outfield infrared images. Then the thermal balance function is constructed, and the ground type is inversed by the hypothesis testing method based on the typical ground optic-electric parameters.
     2. The block matching method is improved to compensate the backgrouond motion quickly. Then, for the single-band IR detection system, the detection algorithm based on region of interest was put forward. Finally, for dual-band infrared detection system, a detection algorithm for ground weak small targets, which integrates the advantages in temporal-spatial domain, is propsed based on fusion of inter-frame difference images. Both of the algorithms can improve the detection capability.
     3. Aimed at the moving surface target, firstly, the round projection vector to compensate the background motion is improved. Then associated with the particle filter, the method combineing detection and tracking the ground moving surface target is proposed. In addition, according to uncertain size of the non-cooperative target, an algorithm is proposed based on the measurement of integrated information, which can not only guarante the detection effectiveness, but also be universal to both small and surface targets.
     4. The impact of imaging conditions on the gray scale of pixels is analyzed. In order to get the real apparent temperature of the background, the IR images are transformed based on the imaging condition. Then the feasure stes can be extracted from the pixel neighboring window, and the target was detected by hypothesis testing with the adaptive window chosen according to different imaging condition.
     5. The range model is founded based on the working principle of the staring IR imaging system. Considered the relationship between the pixel gray and the target’s radiating power, the two ranging algorithms are derived based on one band and two band of the single station. Then the algorithms are validated by the outfield IR image, and the ranging error is analyzed.
     Finally, the composition, function, development and field experiment of the staring infrared detection system is summarized.
引文
[1] Scoggins R.K. Plan for Developing Hierarchical Three-Dimensional Landscape Signature Model. AD-A257550,l992.
    [2] Khale A.B. A Simple Model of the Earth’s Surface for Geologic Mapping by Remote Sensing. Journal of Geophysical Research. 1977,82(11):1673-1680.
    [3] Balick L.K.Thermal Modeling of Terrain Surface Elements.AD-A098019,1981.
    [4] Belmans C. Simulation Model of the Water Balance of a Cropped Soil:SWATRE.J.Hydrol,1983,63:271-286.
    [5] Camillo P.J. Soil and Atmospheric Boundary Layer Model for Evapotranspiration and Soil Moisture Studies. Water Resour. Res. ,1983,V19:371-380
    [6]韩玉阁,宣益民.天然地形的随机生成及其红外辐射特性研究.红外与毫米波学报,2000,19(2):129-138.
    [7]张建奇,方小平,张海兴等.自然环境下地表红外辐射特性对比研究.红外与毫米波学报,1994,13(6):418-424.
    [8] Inclan M.G. A Simple Soil-Vergetation-Atmosphere Model Inter-comparison with Data and Sensetivity Studies. Ann.Geophys. 1993,11:195-203.
    [9] Van de Griend A A.Water and Surface Energy Balance Model With a MuItilayer Canopy Representation for Remote Sensing Porposes.Water Resour. Res. ,1989,25:949-971.
    [10] Lynn B.A. Stomatal Resistance Model Illustrating Plant verus Extenal control Transpiration, Agric.For.Meteoro1.1990,52:5-43.
    [11] Gonda T. Gerhart G R. A Comprehensive Methodology for Thermal Signature Simulation of Targets and Backgrounds. SPIE,1989,1098:23-27.
    [12] Kress M.R. Information Base Procedures for Generation of Synthetic Thermal Scene. AD-A259202,1992.
    [13] Weiss R.A., Sabol B.M., Smith J.A. Physics-Based Infrared Terrain Radiance Texture Model. Final report. AD-A293464,1995.
    [14] Pieter A. Jacobs Write, Wu Wenjiann,Hu Biru,Man Yahui Translate. Thermal Infrared Characterization of Ground Targets and Backgrounds. National Defense Industry Press, Bei Jing. 2004.1.
    [15]于勇.基于特征直线的红外成像目标被动测距方法.舰船电子对抗, 2009. 32(6): 86-90.
    [16]王万平等.被动测距的可观测性分析和滤波方法.红外与激光工程, 2009(6): 1083-1088.
    [17] Wang Wanping, Liao Sheng, Xing Tingwen. Particle Filter for State and Parameter Estimation in Passive Ranging. 2009 IEEE International Conference on Intelligence Computing and Intelligence Systems. 2009.11: 257-261.
    [18]付小宁,吴德怀.只测角的单站三维红外被动测距算法.兵工学报, 2008. 29(10): 1188-1191.
    [19] Banavar S., Raymond E.S. Computer Architectures for Real-time Passive Ranging Algorithm. Digital Avionics Systems Conference , 1993 , 12th.DASC. AIAA/IEEE. 1993,10:292-297.
    [20]吴健飞,李范鸣.三站红外告警系统被动测距方法.红外与激光工程, 2007. 36(4): 560-564.
    [21]浦甲伦,韦常柱,荣思远.修正增益卡尔曼滤波算法在被动测距问题中的应用.宇航学报, 2007. 28(4): 886-889.
    [22]付小宁,刘上乾.基于光电成像的单站被动测距.光电工程, 2007. 34(5): 10-14.
    [23] Pu Jialun, Cui Naigang, Rong Siyuan. Passive Ranging Algorithm in Terms of Polar Coorsinates. Journal of Harbin Institute of Technology. 2009.16(3): 428-430.
    [24]徐志弘,郑猛.基于红外搜索系统的被动测距技术研究.舰船电子工程, 2005. 25(2): 127-130.
    [25]陈志伟等.低空红外预警系统距离估算模型.红外与激光工程, 2004. 33(5): 449-452.
    [26]王学伟,沈同圣与等. IRST被动定位研究.激光与红外, 2001. 31(6): 362-363.
    [27] Hamilton M., Schultheiss P.M. Passive Ranging in Multipath Dominant Enviromens. I. Known to Known Multipath Parameters. IEEE Trans. Signal Processing. 1992,40(1): 1-12.
    [28]吴晗平.红外警戒系统的被动测距方法研究.电光与控制, 1998(3): 21-26
    [29]樊民革,赵剡,孙夏川.基于面积的弹载红外成像被动测距.红外与激光工程, 2009. 38(3): 391-396.
    [30]关松,王巾,高文清.光电被动测距技术研究.光电技术应用, 2007. 22(1): 1-3.
    [31]黄士科,夏涛,张天序.基于红外图像的被动测距方法.红外与激光工程, 2007. 36(1): 109-112.
    [32] Yair Barniv. Application of Velocity Filtering to Optical-Flow Passive Ranging. IEEE Trans. Aerospace and Electronic Systems. 1992.28(4): 957-969.
    [33]陈慧芳,严惠民,姚晓强.被动测距系统汽车目标提取算法研究.浙江大学学报:工学版, 2005. 39(4): 526-529.
    [34]陈朝阳,张桂林.利用成像系统的光学散焦获取景物的深度信息.华中理工大学学报, 1997. 25(12): 8-10.
    [35]付小宁,赵赓,刘上乾.基于对比度的双波段被动红外测距.激光与红外, 2007. 37(6): 517-519
    [36]付小宁,牛建军,刘上乾.红外双波段单站被动测距算法研究.红外与激光工程, 2006. 35(6): 648-651.
    [37]冯国强,邹强,李伟仁.单站双波段红外被动测距算法研究.红外技术, 2005. 27(4): 295-298.
    [38]路远等.地面目标的红外被动测距研究.红外与毫米波学报, 2004. 23(1): 77-80.
    [39]钱铮铁.一种用于红外警戒系统的被动测距方法.红外与毫米波学报, 2001. 20(4): 311-314.
    [40]王兵学,张启衡,陈昌彬,王敬儒,何雪梅.凝视型红外搜索跟踪系统的作用距离模型.光电工程,2004.31(7):8-11
    [41] Gang Wei, Kun-tao Yang. Discussion on operating range of shipborne infrared search-and-track system. 2nd International Symposium on Advanced Optical Manufacturing and Testing Technologies. Optical Test and Measurement Technology and Equipment, Vol. 6150.
    [42]王卫华,牛照东,陈曾平.海空背景凝视红外成像系统作用距离研究.红外与毫米波学报. 2006,25(2):150-153.
    [43] Anders G.M. Dahlberg, Olof Holmgren. Range performance modeling for staring focal plane array infrared detectors. Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVI. Proceedings of SPIE. 2005,Vol.5784,81-90.
    [44] S.Reed, R.M.Gagliardi, Larry Stotts. A recursive moving-target-indication algorithm for optical image sequences. IEEE Trans. on AES, 1990.26(3):434-440.
    [45] S.D. Blostein, T. S. Huang. Detecting small, moving objects in image sequences using sequential hypothesis testing. IEEE Trans. on Signal Processing, 1991. 39(7):1611-1629 .
    [46] S. D. Blostein, Haydn S. Richardson. A sequential detection approach to target tracking. IEEE Trans. on AES, 1994. 30(1):197-212.
    [47] N. Nandhakumar, V. Velten, J. Michel. Thermophysical Affine Invariants from IR Imagery for Object Recognition. IEEE Trans. on PAMI, 1995 .22(8):48–54.
    [48] J. Michel, N. Nandhakumar, V. Velten. Thermophysical Algebraic Invariants from Infrared Imagery for Object Recognition. IEEE Trans. On pattern analysis and machine intelligence.1997,19(1):41-51.
    [49] D. Gregory, Kirk Sturtz, V. Velten,J. Michel, N. Nandhakumar. Dominant-Subspace Invariants. IEEE Trans. On Pattern Analysis and MachineIntelligence.2000, 22(7):649-662.
    [50] N. Nandhakumar. Robust Physics-Based Analysis of Thermal and Visual Imagery. Optical Society of America.1994, 11(11):2981-2989.
    [51] Samuel H. Huddleston, Xin Zhou, William B. Evans, Alice Chan, Michael D. DeVore. Statistical Models for Target Detection in Infrared Imagery. Proc. of SPIE Vol. 6566.
    [52] Reed I S, Gagliardi R M, Shao H M. Application of three dimensional filtering to moving target detection. IEEE Transactions on Aerospace and Electronic Systems. 1983,19(2):899-905.
    [53]张海英,张田文.基于多阶段轨迹融合的交叉多目标检测与跟踪算法[J].电子学报,2005,33(6):1109-1112.
    [54] Markandey V.Motion estimation for moving target detection[J].IEEE Trans on AES,1996,32(3):866-874.
    [55] Alessandro Rossi, Marco Diani, Giovanni Corsini,A technique for ghosting artifacts removal in scene-based methods for non-uniformity correction in IR systems. Electro-Optical and Infrared Systems:Technology and Applications VI,Vol. 7481.
    [56]熊辉,杨卫平,沈振康.红外焦平面阵列非均匀校正算法研究.系统工程与导致技术. 1998. Vol.12:40-43.
    [57] Judith Dijk, Adam W.M. van Eekeren, et al. Performance study on point target detection using super-resolution reconstruction. Automatic Target Recognition XIX. 2009,Vol. 7335.
    [58]龙浦荟,郑南宁,王爱群.基于非均匀采样及注意机制的多分辨率边缘检测.电子学报. 1998. 26(5):97-99.
    [59] Alessandro Rossi, Marco Diani, Giovanni Corsini. Bilateral filter-based adaptive nonuniformity correction for infrared focal-plane array systems. Optical Engineering, 2010.49(5).
    [60]徐军.红外图像中弱小目标检测技术研究西安电子科技大学博士论文, 2003.4.
    [61]郭伟,赵亦工,谢振华,李欣.基于非参数统计的云层描述与红外弱小目标检测.红外与毫米波学报. 2008. 27(5):383-388.
    [62] Askar, H, Xiaofeng Li, Zaiming Li. Performance analysis of dim moving point target detection algorithms. IEEE International Conference on Communications, Circuits and Systems and West Sino Expositions. 2002. Vol.1:605 - 609.
    [63]管志强,陈钱,顾国华,钱惟贤.基于光流直方图的云背景下低帧频小目标探测方法.光学学报. 2008. 28(8):1496-1501.
    [64] ZHao Cui-fang, Shi Cai-cheng, He Pei-kun. Dim Target Detection in Cloud Clutter Image Based on Variogram Function and Rough Set. ICSP2008 Proceedings,2008:1095-1098.
    [65] Liu Jin, Ji Hong-Bing. An Improved Robust Estimation Algorithm for Small IR Target Detection. 2009 IEEE Symposium on Industrial Electronics and Applications (ISIEA 2009),2008:394-398.
    [66]任章,李露,蒋宏.基于红外图像序列的运动目标检测算法研究.红外与激光工程. 2007. 36(12A):136-140Tongzhou Zhao, Shuaijun Ma, Jin Li, et al.Automated object extraction from remote sensor image based on adaptive thresholding technique.MIPPR 2009. Automatic Target Recognition and Image Analysis Authors,Vol. 7495.
    [67]罗军辉,姬红兵,刘靳.基于空间滤波的红外小目标检测算法及其应用.红外与毫米波学报. 2007. 26(3):209-213.
    [68] Jiao Luo, Yuehuan Wang, et al. Scene-adaptive detection and tracking of small target with moving imaging platform.MIPPR 2009. Automatic Target Recognition and Image Analysis .Published 30 October 2009, Vol. 7495.
    [69] S. Kim, Y. Yang and J. Lee. Robust detection of horizontal small targets using synergistic spatial filtering. 29th ELECTRONICS LETTERS, 2009. 45(12).
    [70]胡谋法,陈曾平.基于Zernike-Facet模型和总体最小二乘的弱小目标检测.电子与信息学报. 2008. 30(1):194-197.
    [71] Qian Yu, Isaac Cohen, Gerard Medioni and Bo Wu. Boosted Markov Chain Monte Carlo Data Association for Multiple Target Detection and Tracking , The 18th International Conference on Pattern Recognition (ICPR'06),2006.
    [72] Yuqin Sun, Jinwen Tian, Jian Liu. Background Suppression Based-on Wavelet Transformation to Detect Infrared Target. Proceeding of the Fourth International Conference on Machine Learning and Cybernetics,2005:4611-4615.
    [73]明英,蒋晶珏.基于Cauchy分布的红外视频运动目标检测.红外与毫米波学报. 2008. 27(1):65-71.
    [74] Xinyu Wang, Guilin Zhang and Yirzg Chu. A Robust Approach to The Detection and Tracking of Small Targets with Low Contrast , IEEE Int. Workshop VLSL Design & Video Tech.2005:296~299.
    [75] Wei Kun, Zhao Yongqiang, Pan Quan, Zhang Hongcai. IR Target Detection Based on Kernel PCA and Quadratic Correlation Filters. Fourth International Conference on Image and Graphics,2007:448-452.
    [76] Wei Chang’an and Jiang Shouda. Automatic Target Detection and tracking in FLIR Image sequences using Morphological connected operator , International Conference on Intelligent Information Hiding and Multimedia Signal Processing ,2008:414-417.
    [77]魏坤,赵永强,高仕博,潘泉,张洪才.基于混合概率核主成分二次相关红外目标检测.光子学报. 2008. 37(9):1883-1888.
    [78] Xu Jiping, Ikram-ul-haq, Chen Jie, Dou Lihua, Liu Zaiwen. Moving Target Detection and Tracking in FLIR Image Sequences Based on Thermal Target Modeling. 2010 International Conference on Measuring Technology and Mechatronics Automation. 2010:715-720 .
    [79]吴刚,侯晴宇,武春风,张伟.基于矩的不同地面分辨率红外图像的不变量分析.光学技术. 2007. 33(1):146-151.
    [80]张名成,吴秀清,王鹏伟.基于闭合轮廓提取和部分特征匹配的飞机识别.计算机仿真. 2006. 23(11):193-197.
    [81] Sun-Gu Sun, Dong-Min Kwak, Won Bum Jang, Do-Jong Kim. Small Target Detection Using Center-Surround Difference with Locally Adaptive Threshold. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis (2005):402-407.
    [82] Wei Li, Chunhong Pan, Lixiong Liu. Saliency-Based Automatic Target Detection in Forward Looking Infrared Images. International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009:957-960.
    [83] Q. H. Pham, T. M. Brosnan, and M. J. T. Smith. Sequential digital filters for fast detection of targets in FLIR image data. In Automatic Target Recognition, Proc. SPIE 3069, 1997:62-73.
    [84] Jonah C. McBride, Mark R. Stevens, Ross S. Eaton and Magnús Snorrason. Adaptive infrared target detection. Automatic Target Recognition XIV, Proceedings of SPIE Vol. 5426, 2004:305-314.
    [85] Stauffer, C. and W. Grimson, Adaptive Background Mixture Models for Real-Time Tracking. IEEE Computer Vision and Pattern Recognition, 1999.
    [86] Stauffer, C. and W. Grimson, Adaptive Background Mixture Models for Real-Time Tracking. IEEE Computer Vision and Pattern Recognition, 1999.
    [87] Alexander Tartakovsky. Adaptive sequential algorithms for detecting targets in a heavy IR clutter. In SPIE Proc. Signal and Data Processing of Small Targets (SDPST). Denver, CO, 1999, vol. 3809:231-242.
    [88] Alexander Tartakovsky. Effective adaptive spatial-temporal technique for clutter rejection in IRST. In SPIE Proc. SDPST, Orlando, FL, 2000, vol. 4048:566-576.
    [89] Boris Rozovskii, Anton Petrov and Rudolf Blazek. Interacting banks of Bayesian matcher filters. In SPIE Proc. SDPST, Orlando, FL, 2000, vol. 4048: 601-612.
    [90] Wang Yang,Zhen Qinbo,Zhang Junping.Real-time detection of small target in IR grey image based on mathematical morphology[J] . Infrared and Laser Engineering,2003,32(1):28-31.
    [91] Ye Bin,Peng Jiaxiong.Small target detection based on energy accumulationand order morphology filtering in infrared image[J].Journal of Image and Graphics,2002,7(A)(3):251-255.
    [92] Mahmoud S A.Motion analysis of multiple moving object using hartley transform[J].IEEE Trans on Systems,Man and Cybernetics,1991,21:280-287.
    [93] Mahmoud S A. Motion detection and estimation of multiple moving object in an image sequence using cosine area transform(CAT)[J].IEE Proc,1991,138(5):35l-356.
    [94] Liou. R, Azimi-Sadjadi, M R. Multiple target detection using modified high order correlation. IEEE Trans. AES, 1998, 34(2):553-568.
    [95]卓志敏,杨雷,杨莘元,池庆玺.一种复杂环境下的红外成像运动目标检测方法.宇航学报, 2008, 29(1):339-343.
    [96] Niu Chaoyang, Ma Debao, Zhang Xiangfeng, Zheng Fang. Target Detection and Recognition Based on Polar Decomposition and Haugh Transform. IEEE International Proceeding of Geoscience and Remote Sensing Symposium. 2005,7:4712-4714.
    [97] Sungho Kim, Yukyung Yang, Joohyoung Lee, et al. Robust scale invariant small target detection using the Laplacian scale-space theory. Signal and Data Processing of Small Targets 2008, Vol. 6969.
    [98]刘瑞明,刘尔琦,杨杰,张田昊,王芳琳.核Fukunnaga2Koontz变换检测红外小目标.红外与毫米波学报, 2008, 27(1):47-55.
    [99] Tzannes A P, Brooks D H. Detecting small moving objects using temporal hypothesis testing. IEEE Trans. AES,2002,38(2):570-585.
    [100]王岳环,程胜莲,周晓玮,张天序.基于多级滤波的复杂背景下多尺度小目标检测.红外与激光工程, 2006, 35(3):362-366.
    [101]曹原,杨杰,刘瑞明.基于邻域分析TDLMS滤波器的红外小目标检测.红外与毫米波学报, 2009, 28(3):235-240.
    [102]罗军辉,姬红兵,刘靳,一种基于空间滤波的红外小目标检测算法及其应用,红外与毫米波学报, 2007, 26(3):209-213.
    [103] Jiang Tao, Wang Yong-zhong. Point target detection based on dual-recursive-mean filter [J]. ELECTRONICS OPTICS & CONTROL ,2004,11(3):8-11.
    [104] Salmond D J, Birch H.A., particle Filter for Track-before-detect[A] proc of the American Control Conf[C] A rlington VA, 2001:3755-3760.
    [105]李赣华,董黎,蔡宣平,周东翔,刘云辉.基于SMC的红外序列图像目标检测算法.国防科技大学学报,2007,29(2):65-69.
    [106] Tzannes, A.P., Brooks, D.H. Detection Small Moving objects UsingTemporal hypothesis testing, IEEE Trans on AES. 2002. 38(2):570-585.
    [107] Tantaratana, S., Poor, H.V. Asymptotic relative efficiencies of multistage tests. IEEE Trans. Inform. Theory,1985, 31(5):710-715.
    [108]胡洪涛,敬忠良,胡士强.基于辅助粒子滤波的红外小目标检测前跟踪算法[J].控制与决策,2005,20(11):1208-1211.
    [109] L. A. Johnston. Performance analysis of a dynamic programming track before detect algorithm. EEE Trans. on AES, 2002. 38(1):228-242.
    [110]龙云利,徐晖,安玮,盛卫东.基于分层动态规划的红外弱小目标检测,光电工程,2008,35(11):18-23.
    [111] Wang Xin, Tang Zhenmin. Combining wavelet packet with higher-order statistics for small IR targets detection. Infrared and Laser Engineering, 2008, 38(5):915-920.
    [112]罗子娟,吴一全.基于Contourlet变换的红外图像序列小目标检测技术.信号处理, 2008, 24(4):676-679.
    [113] Song Cheng-tian, Wang Ke-yong. Image Target Detection Using Morphological Neural Network. 2009 International Conference on Computational Intelligence and Security,p234-236.
    [114] Xu Kaiyu, Hu Wenhua, Zhou Weina, Zheng Huayao. Target Detection Based on the Artificial Neural Network Technology. ICARCV 2006.
    [115] Gordon N, Salmond D. Novel approach to non-linear and non-Gaussian Bayesian state estimation [J]. Proc of Institute Electric Engineering, 1993,140 (2): 107-113.
    [116] Arnlampatam M S,Maskell S,Gordon N,et a1.A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking [J]. IEEE Trans.Signal Proc. 2002, 50(2):174-188.
    [117] A. Doucet, N. Gordon, V. Krishnamurthy. Particle filters for state estimation of jump Markov linear systems.IEEE Trans. Signal Processing, 2001, Vol.49, 613-624.
    [118] D. Comaniciu, V.Ramesh, P.Meer. Real-Time Tracking of Non-Rigid Objects using Mean Shift. IEEE Conference on Computer Vision and Pattern Recognition., 2000, II:142–149.
    [119] A. BAL, M. S. Alam, M. S. Aslan. Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter. Automatic Target Recognition XVI,2006,Vol. 6234.
    [120] Jason H. Dixon, Aaron D. Lanterman. Toward practical pattern-theoretic ATR algorithms for infrared imagery. Automatic Target Recognition XVI,2006,Vol. 6234.
    [121] Samuel H. Huddleston, Xin Zhou, William B. Evans, et al. Statisticalmodels for target detection in infrared imagery. Automatic Target Recognition XVII,2007, Vol. 6566.
    [122] Sharif M. A. Bhuiyan, Mohammad S. Alam, Mohamed I. Alkanhal. New two-stage correlation-based approach for target detection and tracking in forward-looking infrared imagery using filters based on extended maximum average correlation height and polynomial distance classifier correlation. Optical Engineering,2007, 46(8):6401-6413.
    [123] Dorin Comaniciu, Visvanathan Ramesh, andPeter Meer, Kernel-Based Object Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence,2003,Vol.25:564-578.
    [124] K. Nummiaro, E. Koller-Meier, L. Van Gool, Object Tracking with an Adaptive Color-Based Particle Filter, First International Workshop on Generative-Model-Based Vision, in conjunction with ECCV’02, 2002,53-60.
    [125] Emilio Maggio, Andrea Cavallaro. Hybrid particle filter and mean shift tracker with adaptive transition model. ICASSP 2005, 221-224.
    [126]宣益民,韩玉阁著.地面目标和背景的红外特性.国防工业出版社,北京. 2004.1.
    [127]魏合理,宋正方.随机风场对自然地表红外辐射统计分布的影响,红外与毫米波学报.1995,14(6): 424-428.
    [128]隋洪智,田国良,李付琴.农田蒸散双层模型及其在干旱遥感监测中的应用.遥感学报,1994,13(6): 220-224.
    [129]张建奇,方小平,张海兴,白长城,杨宜禾.自然环境下地表红外辐射特性对比研究.红外与毫米波学报.1994,13(6):418-424.
    [130] CEDIP Infrared Systems: Camera Characterization Report #293 ,www.cedip-infrared.com,2003,7.
    [131] CEDIP Infrared Systems: Camera Characterization Report #092 ,www.cedip-infrared.com,2002,11.
    [132]白延柱,金伟其.光电成像原理与技术.北京理工大学出版社.
    [133]马文淦,张子平.计算物理学.合肥:中国科学技术大学出版社,1992.
    [134] Kahle Anne B., A Simple Thermal Model of the Earth’s Surface for Geologic Mapping by Remote Sensing, J.Geophys. Res., 1977,82(11):1673-1680.
    [135] M.J.McGuire, J.A.Smith, L.K.Balick, et al. Modeling Direction Thermal Radiance from a Forest Canopy, Remote Sens. Environ. 1989,27(2):169-186.
    [136]田国良,柳钦火,余涛等.热红外遥感.电子工业出版社,北京. 2006.7.
    [137]吕相银,凌永顺,黄超超等.地面目标表面温度及红外辐射的计算.红外与激光工程,2006,36(5):563-567.
    [138]乔平林,张继贤,王翠华,张继刚等.基于遥感数据的非均匀性陆面温度反演方法.红外与激光工程. 2006,35(4):415-418
    [139] N. Nandhakumar, Jonathan D. Michel. Robust Thermophysics-based Interpretation of Radiometrically Uncalibrated IR Images for ATR and Site Change Detection. IEEE Trans on Image Processing. 1997,6(1):65-78.
    [140]曹华梁,丁明跃,周成平等.长波红外图像小目标特性提取方法研究.华中科技大学学报. 2003,31(8):29-30.
    [141]杨德贵,黎湘,庄钊文等.基于统一模型的典型地表红外辐射特性对比研究[J],红外与毫米波学报. 2001,20(4):263-266.
    [142] D. Gregory Arnold, Kirk Skurtz, Vince Velten, N. Nandhakumar. Dominant-Subspace Invariants. IEEE Trans on Pattern Analysis and Machine Intelligence. 2000, 22(7):649:662.
    [143] ZHUO Hongyan,ZHANG Rong, Research of visual range prediction of the target in infrared thermal imaging system ,Multispectral and Hyperspectral image Acquisition and Processing,Proceeding of SPIE,2001,Vol.4548:387-392.
    [144]李润顺,袁祥岩,范志刚,左保军.红外成像系统作用距离的估算.红外与激光工程.2001,30(1):1-4.
    [145]王刚,禹秉熙,基于对比度的空中红外点目标探测距离估计方法.光学精密工程.2002.10(3):276-280.
    [146]王娟,杨春平,吴健.红外热像仪的作用距离估算.电光与控制.2004.11(3):17-19.
    [147]邢强林,黄惠明,熊仁生,于涛.红外成像探测系统作用距离分析方法研究.光子学报,2004.33(7):894-897.
    [148]殷世民,付小宁,刘上乾.对固定平台红外单站被动定位技术研究.光子学报.2004.33(2):237-239.
    [149]辛云宏,杨万海,王保平.一种基于双波段的红外搜索与跟踪系统的单站测距方法.红外技术.2004.26(1):5-8.
    [150]路远,凌永顺,时家明.双波段红外成像系统对空中点目标测距的方法.光学精密工程.2004.12(2):161-164.
    [151] Zhenfeng Shaom, Xianqiang Zhu, CAI Yin. An Adapting Object Detection of Infrared Image Based on Optimal Hybrid Threshold Surface. ICALIP 2008:959-964.
    [152] Duda, R. and P. Hart, Pattern Recognition and Scene Analysis. 1973, New York, NY: Wiley.
    [153] Der,S., et al., Scale-Insensitive Detection Algorithm for FLIR Imagery. 2001, ARL.
    [154] Schachter, B.J. A Survey and Evaluation of FLIR Target Detection/Segmentation Algorithms. In Image Understanding Workshop. 1982: MorganKauffman.
    [155] Burton, M. and C. Benning. Comparison of imaging infrared detection algorithms. In Infrared Technology for Target Detection and Classification. 1981: SPIE.
    [156]马东辉,朱斌,樊祥,任彪.基于粒子滤波的目标图像多特征融合跟踪方法[J].探测与控制学报,2009,31(4):39-43.
    [157] Aksoy, S. and R.M. Haralick, Feature normalization and likelihood-based similarity measures for image retrieval.Pattern Recognition Letters, 2001. 22(5): 563-582.
    [158] Alter, T.D. and W.E.L. Grimson. Verifying model-based alignments in the presence of uncertainty. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Proceedings. 1997,6:344-349
    [159] Otsu, N., A Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems, Man, and Cybernetics, 1979. 9(1): 62-66.
    [160] Sungu Sun. Target detection using local fuzzy thresholding and binary template matching in forward-looking infrared images.Optical Engineering. 2009,46(3):6402-6410.
    [161]潘锋,王宣银等.一种新的运动目标检测与跟踪算法[J].光电工程,2005,32 (1) :43-46.
    [162] Sasa G, Loncaric S. Spatio-temporal image segmentation using optical flow and clustering algorithm[C]. Proceedings of the First International Workshop on Image and Signal Processing and Analysis, IWISPA 2000:63-68.
    [163] Markandey V,Reid A , Shenq Wang. Motion estimation for moving target detection [J]. IEEE Transactions on Aerospace & Electronic Systems Society.1996.32(3):866-874.
    [164] KimJ B. Efficient region based motion segmentation for video monitoring system [D]. Kyungpook National University, 2001.
    [165]陈忠碧,张启衡等.基于块估计的运动目标检测方法[J].光电工程,2006 ,33 (1) :15-19.
    [166]于成忠,朱骏等.基于背景差法的运动目标检测[J].东南大学学报(自然科学版) , 2005,35 (2) :159-161.
    [167] S. Zhu and K. K.Ma. A new diamond search algorithm for fast block-matching motion estimation. IEEE Trans. Image Processing, 2000,Vol.9:287-290.
    [168] J.Y. Thanm, S.Ranganath, M.Ranganath, and A.A. Kasim, A novel unrestricted center-biased diamond search algorithm for block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 1998.Vol.8:369-377.
    [169] S. Zhu and K .K .Ma. A new diamond search algorithm for fast block-matching motion estimation. IEEE Trans. Image Processing, 2000,Vol.9:287-290
    [170] C. Zhu, X.Lin, L.P.Chau. Hexagon-Based Search Patten for Fast Block Motion Estimation,IEEE Transactions on CSVT, May2002, 12(5):349~355.
    [171]王旸,冯驰.基于块匹配的电子图像稳定算法.咸阳师范学院学报. 2006,21(8):36-38.
    [172] Lee T Y, et al. Non-lambertian effects on remote sensing of surfacere flectance and vefetation index [J]. IEEE Trans. on GRS.1985, 24 (5): 699-708.
    [173] Guixi Liu, Xianhong Liu, Mingli Shao, et al.A novel fusion scheme for infrared and visual images based on wavelet and color transfer algorithm. 2nd International Symposium on Advanced Optical Manufacturing and Testing Technologies. Optical Test and Measurement Technology and Equipment .Vol. 6150.
    [174] Cheng Zhao, Mengyin Fu. Fusion of infrared and visual image sequences based on moving target detection and DT-CWT. MIPPR 2009. Automatic Target Recognition and Image Analysis .Vol. 7495.
    [175] Yuchi Lin, Le Song, Xin Zhou, et al.Infrared and visible image fusion algorithm based on Contourlet transform and PCNN. Infrared Materials, Devices, and Applications.Vol. 6835.
    [176] Alexander T. Detection of dim point targets in cluttered maritime backgrounds through multisensor image fusion [J]. Proceedings of SPIE. 2002, 4718: 118-129.
    [177]郑林,韩崇昭,左东广等.基于多特征融合的运动目标识别[J].系统仿真学报. 200405, 16(5): 1081-1084.
    [178] Sun Y, Zheng Y, Tian J, et al. Dim Small Targets Fusion Detection on Infrared Image[Z]. Kun ming: 2008,07:12-15.
    [179]孙玉秋,田金文,柳健.基于小波变换的双色红外图像融合检测方法[J].红外与激光工程. 2007, 36(2): 240-243.
    [180] Yuqiu Sun, Jinwen Tian, Jian Liu.Novel method on dual-band infrared image fusion for dim small target detection (Journal Paper). Optical Engineering.2007,46(11):402-409.
    [181] U. Adomeit, R. Ebert.Improved target detection by IR dual-band image fusion. Electro-Optical and Infrared Systems. Technology and Applications VI.2009 .Vol. 7481.
    [182] Yuqiu Sun, Shalan Li, et al. LS-SVM based dim and small infrared target dualband fusion detection .Second International Conference on Space Information Technology.Vol. 6795.
    [183]史泽林,魏颖,黄莎白.基于小波互能量交叉的复杂背景中红外小目标检测方法[J].弹箭与制导学报. 2003, 23(4): 55-58.
    [184]孙翠娟.复杂背景条件下的红外运动小目标检测技术研究[D].长沙:国防科技大学, 2002.11.
    [185]王卫华,牛照东,陈曾平.基于时空域融合滤波的红外运动小目标检测算法[J].红外与激光工程. 2005, 34(6): 714-717.
    [186] Chi J.N., Fu P., Wang D.S., et al. A detection method of infrared image small target based on order morphology transformation and image entropy difference [J]. Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on. 2005, 8: 5111-5116.
    [187] Vella F.,Castorina A.,Mancuso M.,et al. Digital image stabilization by adaptive block motion vectors filtering.IEEE Trans on Consumer Electronics,2002,48(3):796-801.
    [188] Uomori K., Morimura A., Ishii H., et al. Automatic images stabilizing system by full digital signal processing. IEEE Transon Consumer Electronics, 1990, 36(3):510-519.
    [189] Sauer K., Schwartz B.Efficient block motion estimation using integral projections.IEEE Trans on Circuits and Systems for Video Technology, 1996, 6(5):513-518.
    [190] Censi A., Fusiello A. Image Stabilization by features tracking. 10th International Conference on image analysis and processing. Venice Italy, 1999, 12:665-667.
    [191] Mohamed S., Yasein, Pan Agathoklis. An improved algorithm for image registration using robust feature extraction. In Proceedings of the IEEE Canadian Conference on Electrical and Computer Engineering, Saskatoon, Saskatchewan, Canada, May. 2005.
    [192] Mohamed S. Yasein, Pan Agathoklis. Automatic and robust image registration using feature points extraction and Zernike moments invariants. In Proceedings of the IEEE International Symposium on Signal Processing and Information Technology.2005.
    [193]罗诗途,张圮,王艳玲,罗飞路.一种基于特征匹配的实时电子稳像算法[J].国防科技大学学报,2005,27(3):45-48.
    [194] Siwaphon Chunhavittayatera, Orachat Chitsobhuk, Kiatnarong Tongprasert. Image Registration using Hough Transform and Phase Correlation. ICACT 2006, 2:973-977.
    [195] George Lazaridis, Maria Petrou. Image Registration Using the Walsh Transform. IEEE Transactions on Image Processing, 2006, 15(8):2343-2357.
    [196]徐亦斌,王敬东,李鹏.基于圆投影向量的景象匹配方法研究[J].系统工程与电子技术,2005,27(10):1725-1728.
    [197] M. Sanjeev Arulampalam, Simon Maskell, Neil Gordon, and Tim Clapp, A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking,IEEE Trans. On Singal Processing, 2002, 50(2):174~188.
    [198]程建,周越,蔡念,杨杰,基于粒子滤波的红外目标跟踪.红外与毫米波学报. 2006,25(2):113-117.
    [199] P´rez, P., Hue. C, Vermaak, J., Gangnet, M. Color-Based Probabilistic Tracking. European Conference on Computer Vision, 2002, Vol.1: 661-675.
    [200] D. Casasent and J. Smokelin, Real, imaginary, and clutter gabor filter fusion for detection with reduced false alarm, Opt, Eng.1994,33(7): 2255–2263.
    [201] T. Kailath. The Divergence and Bhattacharyya Distance Measures in Signal Selection, IEEE Transactions on Communication Technology, 1967, COM-15, 52~60.
    [202]李静,陈兆乾,秦小麟.基于粒子滤波算法的非刚性目标实时跟踪.南京航空航天大学学报[J],2006, 38 (6):775-779.
    [203]徐蓉萍,杨磊.红外复杂背景中一种融合两类跟踪框架优点的小目标跟踪算法[J].红外与毫米波学报,2008,27(5):354-360.
    [204] Shiozaki A. Edge extraction using entropy operator. CVGIP Proc, 1986,36:1-9.
    [205]李龙,李俊山,叶霞.基于Mean Shift算法的运动平台下红外目标跟踪[J].红外与激光工程,2007,36(2):229-232.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700