用户名: 密码: 验证码:
光电跟踪设备低对比度目标捕获能力检验方法研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
低对比度目标捕获能力是衡量光电跟踪设备总体性能的重要内容之一。国内对该项能力的检验一般在外场进行,但外场检验往往不能定量,且通常需要众多的人力、物力,同时也不适用于批量产品的检验。
     针对光电跟踪设备低对比度目标捕获理论尚不完善,论文对捕获理论进行了研究,总结出了动态灰度、动态对比度公式并进行了相关实验验证。光电跟踪设备低对比度目标捕获能力理论公式的建立和完善,有助于实现光电跟踪设备低对比度目标捕获能力的检验。
     针对光电跟踪设备低对比度目标捕获能力室内检验方法欠缺的问题,论文介绍了应用可调对比度无穷远目标源装置和可调整转台,建立光电跟踪设备低对比度目标捕获能力检验系统,检验系统利用大小两个积分球分别模拟对比度连续可调、可测的均匀目标和均匀背景,利用精密转台建立检验系统所需的动态环境,根据被检设备对该动态目标的提取情况来检验光电跟踪设备低对比度目标的捕获能力。
     论文对检验装置进行相应的标定,对可调对比度目标源装置进行了图像与辐亮度的均匀性检验实验,确保对比度目标能够满足光电跟踪设备低对比度目标捕获的需求。对检验装置模拟出的目标与背景进行了准确性验证,排除了检验装置间各设备的相互干扰影响检验结果的可能性。
     规定了采用以物方辐亮度为参数的对比度标定公式,论证了对比度标定公式与传统像方对比度公式之间的联系,并进行了实验验证。
     应用光电跟踪设备低对比度目标捕获的基本理论,应用检验系统对某光电跟踪设备的低对比度静态、动态目标捕获能力进行了检验。检验结果说明,论文所介绍的检验方法、检验装置能够检验光电跟踪设备低对比度静态目标捕获能力;能够对具有低速、低对比度需求的光电设备低对比度目标捕获能力进行检验。
Low contrast target acquisition ability is one of the important factors relating tooverall performance of photoelectric tracker. Domestic assessment of low contrasttarget acquisition ability is usually carried out from field experiments; however, fieldtest not only always has poor capability of quantitatively assessment, but also oftenneeds so much manpower and material resources that field test is not suitable forbatch test.
     Because of its imperfect theory of low contrast target acquisition forphotoelectric tracker, capture theory is studied in this dissertation. The dynamic grayformula and the dynamic contrast ratio formula is summarized and tested. Perfecttheory of low contrast target acquisition for photoelectric tracker helps assessmentlow contrast target acquisition ability for photoelectric tracker
     Aiming to the lack of indoor test methods relating to low contrast targetacquisition ability for photoelectric tracker and the imperfect theory about lowcontrast target acquisition, a new indoor method for performance assessment of lowcontrast target acquisition ability for photoelectric tracker is proposed in thisdissertation. Infinity target source of adjustable contrast and turntable of adjustablespeed are considered as detection device. Optical reference target whose contrast canbe accurately measured is provided for detecting opto-electronic tracker working indynamic environment where the rotation rate can be precisely set, in order to validate acquisition ability of opto-electronic tracker for low contrast dynamic object based ontarget extraction. The opto-electronic tracker can also be evaluated in terms ofacquisition performance or acquisition speed in different target contrast and differentmovement speed by the analysis of the target's movement speed, target size that affecttarget contrast.
     Assessment device is proved well in this dissertation, and experiment for proveimage and radiance of target and background in adjustable contrast target source isperformed. In order to make contrast targets meet the needs of low contrast targetscapture photoelectric tracker, the accuracy of assessment device's target andbackground is verified, the possibility of mutual interference between differentequipment which affect the evaluation results is ruled out.
     Contrast calibration formula use radiance as parameters in this dissertation. Therelationship between contrast calibration formula and tradition contrast formula isDemonstrated and tested.
     The basic theory of low contrast targets capture is applied to assessment of lowcontrast static and dynamic target acquisition capability for a certain photoelectrictracker by assessment device. Assessment result shows that assessment method andassessment device presented in this dissertation can assess the low contrast statictarget acquisition ability for photoelectric tracker; and it has the capability to assessthe low contrast dynamic target acquisition ability for photoelectric tracker with lowspeed, low contrast demand.
引文
[1]吴培.基于滑模变结构控制的光电经纬仪目标捕获动态性能研究[D]:[硕士学位论文].吉林:长春光学精密机械与物理研究所,2010.
    [2]王建立.光电经纬仪电视跟踪捕获快速运动目标技术的研究[D]:[博士学位论文].吉林,长春光学精密机械与物理研究,2002.
    [3]唐九华,轨道测量光学仪器[J],光学机模,1980,(04)
    [4]李连学,曹秋生,光电跟踪仪的自主捕获技术研究[J].激光与红外,2006,36(12),1142~1145.
    [5] Richard L. Espinola, Jae cha, Modeling the performance of turbulence mitigationalgorithms in targeting imagers[J], OSA/IS,2010.
    [6]中华人民共和国国家军用标准,电视跟踪器通用规范,1993,12
    [7]叶露光电跟踪设备低对比度目标捕获能力评价方法研究[J],光学学报,201232(11),1115001-1~5.
    [8]王素华,沈湘衡,叶露,可调对比度目标源装置中对比度的标定[J],光学精密工程,2012,Vol.20,No.5.949-956.
    [9] Bahadir Karasulu, Serdar Korukoglu,Moving object detection and tracking byusing annealed background subtraction method in videos Performanceoptimization[J],Expert Systems with Applications39(2012)33–43,Elsevier Ltd,2011.
    [10]张宁,利用动态靶标装置的光电经纬仪跟踪性能评价研究,[D]:[博士学位论文],吉林,长春光学精密机械与物理研究,2010.5.
    [11]熊艳,张桂林,彭嘉雄.自动目标识别算法性能评价的一种方法[J].自动化学报,1996,22(2):190-195.
    [12]周进,吴钦章,弱小目标跟踪算法性能评估的研究[J].光电工程,2007,34(1),19-22.
    [13]胡文钢,汪岳峰,电视跟踪箱跟踪情能检测仪设计[J],光电子技术与信息,2005,18(1),61~64
    [14]Keith krapels, Ronald G. Driggers, Target-acquisition performance inundersampled infrared imagers: static imagery to motion video[J],2005, Appliedoptics,44(33),7055~7061.
    [15]张宁,沈湘衡.基于等效正弦、等效目标法的直线动靶标建模实现[J].激光与红外,2008,38(2):154-157.(中文核心).
    [16]张宁,杨亮,沈湘衡.动态靶标实时引导数据的产生与传输[J].计算机测量与控制,2008,16(12):1884-1885.(中文核心)
    [17]Zhang ning,SHEN Xiang-heng.System Identification of Tracking Error andEvaluation of Tracking Performance Using BP Neural Network[C].Proc of SPIE,2009,Vol7383:73832F1-9.(EI)
    [18]张宁,沈湘衡,杨亮.应用跟踪误差等效模型的光电经纬仪跟踪性能评价[J].光学精密工程,2010,18(3):677-684.
    [19]张宁,沈湘衡,杨亮,谢明明.利用动态靶标谐波特性的光电经纬仪跟踪性能评价[J].光学精密工程,2010,6.
    [20]杨亮,沈湘衡,张宁.Angular Rate of Test Table based on High-speed Non-ContactMeasurement,第九届国际电子测量与仪器学术会议,2009.8.
    [21]S. M. Pizer, J. B. Zimmerman, E. V. Staab. Adaptive grey level assignment in CTscan display[J]. Compute. Assist. Tomogr.1984,8(2):300-305.
    [22]S. M. Pizer, E. P. Amburn, J. D. Austin. Adaptive histogram equalization and itsvariations. Compute.Vision. Graphics Image Processing,1987,39:355-368.
    [23]R. H. Sherrir, G. A. Johnson.Regionally adaptive histogram equalization of thechest. IEEE Trans. Med. Imag,1987,6:1-7
    [24]D. Mukherjee, B. N. Chatterji. Adaptive neighborhood extended contrastenhancement and its modefications. Graphical medels and image processing,1995,57(3):254-265.
    [25]J. S. Lee. Digital image enhancement and noise filtering by using local statistics.IEEE Trans.Pattern Anal. Machine Itell,1980, PAMI-2:165-168.
    [26]V. Digalakis, D. G. Manolakis, V. K. Kok. Automatic adaptive contrastenhancement for radiological imaging. IEEEint. Symp. Circurits Syst,1993,810-813
    [27]G. Deng, L. W. Cahill, G. R. Tobin. The study of logarithmic image processingmodel and its appaplication to image enhancement. IEEE Trans. Image Processing,1995,4(4):506-512.
    [28]H. Zhu, F. H. Y. Chan, F. K. Lam. Image contrast enhancement by constrainedlocal histogram equalization. Computer vision and image understanding,1999,73(2):281-290.
    [29]Fabrizio Russo. An Image Enhancement Technique Combining Sharpening andNoise Reduction, IEEE Transactions on Instrumentation and Measurement,2002,52(4):824-828
    [30]Sabine Dippel, Martin Stahl, et al. Multiscale Contrast Enhancement forRadiographics: Laplacian Pyramid Versus Fast Wavelet Transform, IEEE Transactionson Medical Imaging,2002,21(4):343-353.
    [31]T. Parag, A. Elgammal, and A. Mittal. A Framework for Feature Selection forBackground Subtraction. IEEE International Conference on Computer Vision andPattern Recognition,2006,2:1916-1923.
    [32]H. Grabner and Horst Bischof. Online Boosting and Vision. IEEE InternationalConference on Computer Vision and Pattern Recognition,2006,1:260-267.
    [33]W.Z. Hu, H.F Gong and S.C Zhu. An Integrated Background Model for VideoSurveillance Based on Primal Sketch and3D Scene Geometry. IEEE InternationalConference on Computer Vision and Pattern Recognition,2008.
    [34]Y. Sheikh and M. Shah. Bayesian Modeling of Dynamic Scenes for ObjectDetection. IEEE Transactions on Pattern Analysis and Machine Intelligence,2005,22(11):1778-1792.
    [35]B. Han, D. Comaniciu, and L. Davis. Sequential Kernel Density Approximationthrough Mode Propagation: Applications to Background Modeling. Asian Conferenceon Computer Vision,2004.
    [36]M. Piccardi and T. Jan. Mean-Shift Background Image Modeling. IEEEInternational Conference on Image Processing,2004:3399-3402
    [37]Y.L. Tian, M. Lu, A. Hampapur. Robust and Efficient Foreground Analysis forReal-time Video Surveillance. IEEE International Conference on Computer Visionand Pattern Recognition,2005,1:1182-1187
    [38]M. Heikkila and M. Pietikainen. A Texture-Based Method for Modeling theBackground and Detecting Moving Objects. IEEE Transactions on Pattern Analysisand Machine Intelligence,2006,28(4):657-662.
    [39]J. Yao and J.M. Odobez. Multi-Layer Background Subtraction Based on Colorand Texture. IEEE International Conference on Computer Vision and PatternRecognition,2007:1-8.
    [40]G. Dalley, J. Migdal and W. Eric L. Grimson. Background Subtraction forTemporally Irregular Dynamic Textures. Proceedings of the IEEE Workshop onApplications of Computer Vision,2008.
    [41]M. Seki, T. Wada, H. Fujiwara and K. Sumi. Background Subtraction Based onCooccurrence of Image Variations. IEEE International Conference on ComputerVision and Pattern Recognition,2003,2:65-72
    [42]K.A. Patwardhan, G. Sapiro and V. Morellas. Robust Foreground Detection inVideo Using Pixel Layers. IEEE Transactions on Pattern Analysis and MachineIntelligence,2008,30(4):746-751.
    [43]A. Monnet, A. Mittal, N. Paragios, and R. Visvanathan. Background Modelingand Subtraction of Dynamic Scenes. IEEE International Conference on ComputerVision,2003,2:1305-1312.
    [44]J. Kato, T. Watanabe, S. Joga, J. Rittscher, and A. Blake. An HMM-BasedSegmentation Method for Traffic Monitoring Movies. IEEE Transactions on PatternAnalysis and Machine Intelligence,2002,24(9):1291-1296.
    [45]Comaniciu D,Ramesh V,Meer P. Kernel-based object tracking[J]. IEEETransactions on Pattern Analysis and Machine Intelligence,2003,25(5):564-577.
    [46]Comaniciu D,Ramesh V,Meer P. Real-time tracking of non-rigid objectsusing mean shift[C]//Proceedings of the IEEE Computer Society Conference onComputer Vision and Pattern Recognition. Hilton Head Island: IEEE,2000:142-149.
    [47]M. J. Black, P. Anandan. The Robust Estimation of Multiple Motions: Parametricand Piecewise-Smooth Flow Fields. Computer Vision and Image Understanding.1996,63(1):75-104
    [48]R. Szeliski, J. Coughlan. Spline-Based Image Registration. International Journalof Computer Vision,1997,22(3):199-218
    [49]J. L. Barron, D. J. Fleet and S. S. Beauchemin. Performance of Optical FlowTechniques. International Journal of Computer Vision.1994,12(1):43-77
    [50]J. Wang, E. Adelson. Representing moving images with layers. IEEE Transactionson Image Processing,1994,3(5):625-638
    [51]Y. Wang, O. Lee. Active Mesh: A Feature Seeking and Tracking Image SequenceRepresentation Scheme. IEEE Transactions on image Processing,1994,3(5):610-614.
    [52]Lance M. Simms,Autonomous subpixel satellite track end point determinationfor space-based images[J], APPLIED OPTICS,2011,50(22).
    [53]Aurora Fassi, Marco Riboldi, Christian Fabio Forlani, Guido Baroni, Optical eyetracking system for noninvasive and automatic monitoring of eye position andmovements in radiotherapy treatments of ocular tumors[J], APPLIEDOPTICS,2012,51(13)
    [54]D. J. Townsend, P. K. Poon, S. Wehrwein, T. Osman, A. V. Mariano, E. M. Vera,M. D. Stenner, and M. E. Gehm, Static compressive tracking[J], OPTICS EXPRESS,2012,20(19).
    [55]钟必能,复杂动态场景中运动目标检测与跟踪算法研究[D],[博士学位论文],黑龙江,哈尔滨工业大学,2010.9.
    [56]刘贵喜,杨万海,基于多尺度对比度塔的图像融合方法及性能评价[J],光学学报,2001,Vol.21,No.11.1336-1342.
    [57]Brian W. Pogue, Scott C. Davis, Xiaomei Song, Ben A. Brooksby, HamidDehghani, Keith D. Paulsen, Image analysis methods for diffuse opticaltomography[J], SPIE, Journal of Biomedical Optics,11(3),2006.
    [58]Brett A. Sickmiller, Denis W. Oesch, Darry J. Sanchez, and Patrick R. Kelly, HighContrast Imaging in the Presence of Turbulence[J], Proc. of SPIE Vol.838083800F,2012.
    [59]Keith J. Rebello, Jeffrey P. Maranchi, Jason E. Tiffany, Christopher Y. Brown,Adam Maisano, Matthew A. Hagedon, Jason C. Heikenfeld, Electrofluidic systems forcontrast management[J], Proc. of SPIE Vol.8373,83731A,2012.
    [60]Kenneth Ranney, Anthony Martone, Roberto Innocenti, Lam Nguyen,Contrast-Based Moving Target Detection with the Randomized Linear ReceiveArray[J], Proc. of SPIE Vol.8361,83611K,2012.
    [61]金海燕,刘芳,焦李成,基于多尺度对比度塔和方向滤波器组的图像融合[J],电子学报,2007,35(7).
    [62]刘必鎏,时家明,赵大鹏,张玮,目标与背景的对比度分析及应用[J],航天电子对抗,2007,Vol.24,No.3.48~51.
    [63]范媛媛,沈湘衡,桑英军,基于对比度敏感度的无参考图像清晰度评价[J],光学精密工程2011,Vol.19,No.10.2485-2493.
    [64]范媛媛,沈湘衡,桑英军,对比敏感下的图像对比度评价[J],沈阳建筑大学学报(自然科学版),2012,Vol.28,No.1.187-192.
    [65]张亚涛,吉书鹏,王强锋,郭正玉,基于区域对比度的图像清晰度评价算法[J],应用光学,2012,Vol.33,No.2.293-299.
    [66]聂守平,王鸣,刘峰,低对比度图像分割算法研究[J].中国激光,2004,31(1):89~91.
    [67]张小虎.靶场图像运动目标检测与跟踪定位技术研究.国防科学技术大学博士论文.2006.
    [68]于浩,CCD相机测量对比度的校正方法研究[D],长春理工大学硕士学位论文,2010.
    [69]田园,CCD图像对比度测试方法研究[D],长春理工大学硕士学位论文,2008.激光与光电子学进展,2011,48(6)
    [70]李志宏,雷美容,周学艳,王菲,杨进华,基于CCD的目标与背景对比度测量与实验校正[J],长春理工大学学报(自然科学版),2008,31(1).
    [71]刘扬,于浩,邸旭,用数字图像实现对比度测量及其矫正方法研究[J],长春理工大学学报(自然科学版),2009,32(4).
    [72]张以谟,应用光学[M],北京,机械工业出版社,1982,102~103.
    [73]安连生,李林,李全臣,应用光学(第三版)[M],北京,北京理工大学出版社,1997,103~126.
    [74]Li Peihua, A clustering-based color model and integral images for fast objecttracking[J],2006Elsevier, Signal Processing: Image Communication21(2006)676–687.
    [75]Jen-Chao Tai, Shung-Tsang Tseng, Ching-Po Lin, Kai-Tai Song, Real-time imagetracking for automatic traffc monitoring and enforcement applications2003Elsevier,Image and Vision Computing22(2004)485–501.
    [76]孟勃,朱明, MS MC跟踪算法在目标跟踪中的应用[J],光学精密工程,2008,16(1).
    [77]王国良,刘金国,基于粒子滤波的多自由度运动目标跟踪[J],光学精密工程,2011,19(4).
    [78]李国宁,刘妍妍,金龙旭,用于动态目标跟踪的面阵CCD成像系统[J],光学精密工程,2008,16(3).
    [79]William priedhorsky, Jeffrey J. Bloch,Optical detection of rapidly moving objectsin space[J], Applied Optics,2005,1,20,Vol.44, No.3.
    [80]孟希羲,冯华君,徐之海,李奇,陈跃庭,基于面阵CCD的时间延时积分模式的空间相机自动对焦[J],光学学报,201131(11),1128002-1~7.
    [81]孟希羲,基于图像配准的空间相机自动对焦[D],浙江大学硕士学位论文,2012.
    [82]王家骐,任建缶,尤英奇,刘光亚,低飞小目标电视跟踪作用距离分析[J]光学学报1994,14(5).
    [83]马佳光.捕获跟踪与瞄准系统的基本问题[J].光电工程,1989,16(3):3-34.
    [84]田少文,马彩文,吴圣雄.光电经纬仪的跟踪误差及其检测[J].光子学报,1997,26(11):1041-1045.
    [85]张耀,雍杨,张启衡,徐智勇,严棚,魏宇星,低对比度小目标检测[J],强激光与粒子束,2010,Vol.22,No.11.2566-2570.
    [86]严世华,何永强,周玉龙,基于红外鱼眼探测系统的运动目标模型[J],光学学报,201232(9),0911002-1~6
    [87]于起峰,陆宏伟,刘肖琳.基于图像的精密测量与运动测量[J].科学出版社,2002.
    [88]李清军.快速视频判读方法的研究.[J].光学精密工程,2000,4:321-324
    [89]焦斌亮,闫旭辉,基于TDI-CCD成像像移分析及图像复原[J],宇航学报,2008,29(2).
    [90]叶露,谷立山,沈湘衡,可调对比度光沈无穷远目标源设计[J]应用光学201031(5):681-684.
    [91]Arthur G.Prediction and measurement of minimum resolvable contrast for TVsensors[J].Proc SPIE,1994,2223:533—541.
    [92]Jenquin MJ.A Bridge Between Modulation Transfer Function and MinimumResolvable Contrast[J].Proc SPIE,1995,2470:380—385.
    [93]Bijl P, Valeton JM. Triangle orientation discrimination: the alternative tominimum resolvable temperature difference and minimum resolvable contrast[J].optEng,1998,37(7):1976—1983.
    [94]BijlP, Valeton JM.Bias—free procedure for the measurement of the minimumresolvable temperature difference and minimum resolvable contrast[J].opt Eng,1999.38(10):1735—1742.
    [95]Zhou Yan, Jin Weiqi, Gao Zhiyong, Minimum Resolvable Contrast(MRC)Studyfor CCD Low Light Level Imaging System[J].Proc SPIE,2002,4925:591—597.
    [96]Bijl P, Valeton JM.TOD, A New Method to Characterize Electro—optical SystemPerformance[J]. Proc SPIE,1998,3377:182—193.
    [97]Li Wen juan, Qi Ch ao, Dai Jingmin. Realizing variable contrast technique inMRC measuring target using integrating sphere[J]. Chin opt Lett,2004,2(9):524—527.
    [98]李文娟,张元,戴景民,陈应航,可见光成像系统MRC测试技术的研究[J].计量学报,2006.1, Vol.27, No.1:32~35.
    [99]TIM B, ALAN I, PAUL B, et al. Advanced test systems for production testing ofcamer as with day/night and visible/NIR capabilities [J]. Proc. Of SPIE,2005,5784:272-279.
    [100] LABSPHERE. A guide to integration sphere radiometer and photometer[DB/OL]. NORTH SUTTONNH: LABSPHERE.2009.http://www.labsphere.com/tecdocs aspx.
    [101]胡家升.光学工程导论[M].大连:大连理工大学出版社,2006.
    [102]李载峰,李俊霖,对比度可调目标源电控系统[J],长春工业大学学报(自然科学版))2012,33(4).
    [103]贺代春.基于RS485的自来水厂监控系统设计[J].重庆科技学院学报自然科学版2010(1):140-142.
    [104]郭庆亮.利用RS485实现多路温度测量[J].电子产品世界2010(3).48-50.
    [105]曾敬.基于485总线的联网报警控制系统的实现[J].信息与电脑2010(7),39.
    [106]史东辉.使用统计变异指标研究离群数据挖掘方法[J].计算机工程与应用,2009,45(17):125-128.
    [107] Toet A. Multiscal contrast enhancement with application to image fusion. Opt.Engng.,1992,31(5),1026~1031.
    [108]李成,鞠明,毕笃彦,刘波,基于局部自适应拉窗的复合图像增强算法[J],光学学报,2009,Vol.29,No.10.2756~2761
    [109] Sos S. Agaian, Blair Silver, Karen A. Panetta. Transform coefficienthistogram-based image enhancement algorithms using contrast Entropy[J],IEEE Trans.On Image Processing,2007,16(3),741~758
    [110]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[J],光学精密工程2002,Vol.10,No.3.276~280
    [111] Philip N,Slater. Remote Sensing, optics and optical systems[M],Massachusetts,Addison-wesley publishing company,1980.
    [112]吕俊伟,何友金,韩艳丽,光电跟踪测量原理[M],北京,国防工业出版社,2010.

© 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