基于遥感图像的子母弹机场毁伤的效果分析研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
适时、准确的打击效果评估对决策后续战役行动、加速战役进程、节约战争成本具有十分重要的作用。由于现代战争中,夺取制空权已成为影响战争进程的关键,所以作为空军执行作战任务唯一依托的机场就自然成了打击的焦点。基于此,本文针对机场这一典型军事目标,将数字图像处理技术和数据挖掘技术运用到机场的毁伤分析中,对机场毁伤效果进行了研究。
     机场毁伤识别作为模式识别领域的问题之一,在军事上有着重要的应用前景。本文结合一些己有的方法,研究了有关遥感图像下机场被子母弹毁伤的识别方法并通过数据挖掘的方法对检测出来的毁伤进行了进一步分析。
     由于实验条件的限制,本文首先建立了子母弹数学模型,通过计算机仿真的方法模拟打击效果。为了得到更好的识别效果,本文使用灰度变换对遥感图像进行预处理,增强了要检测的毁伤部分与其他部分的对比度。在识别之前,使用种子填充的方法从图像中提取出机场跑道掩模图像,使识别范围限制在我们感兴趣的跑道上。本文结合子母弹毁伤遥感图像毁伤的特点提出了一种基于邻域灰度特征的毁伤检测算法。并结合变化检测的方法实现了基于双幅图像的毁伤检测。识别后通过聚类算法对识别结果进行进一步的分析。结合本文研究的毁伤的特点,本文对基于遗传算法的k-mediods聚类算法和对k均值聚类算法进行了改进,使得这两种算法都具有自动确定分类数的功能并在实验中取得了很好的效果。
Timely, accurate assessment of the impact plays a very important role in thecampaign after decision-making.It can also accelerate the process and save war cost.inthe modern war, seizing control of the air war has become the key to theprocess.Therefore,as the Air Force is only rely on the airport, naturally the airportbecome the focus of attacking. Based on this,this paper uses digital image processingtechniques and data mining technology in airport damage analysis to study.
     As one of the issues in the field of pattern recognition, airdrome destructiondetection has important applications in the military field. In this paper, we make someresearches and progress on the detection of destruction of airdromes which were attackedby cluster-warhead. The images that we used are remote sensing images .Besides that, wehave done some further analysis to the destruction by methods of data mining.
     Since restricting of testing condition,a mathematical model of cluster-warhead ismade to simulate the result of attacking by cluster-warhead.In order to get a betterresult of recognization,gray transform is used to enhance the image.Before recognization,seed filling algorithm is used to extract airport runways mask image,so that we can getthe part that we interested in. In this paper, we proposed a neighborhood -based damagedetection algorithm referring to the gray characteristic of airdrome destruction bycluster-warhead in remote sensing images .Besides that, with combination of changedetection and this algorithm,we get a method to detect destruction on the dualimages.Then ,we use cluster algoritms to analysis the result of the last step.In thispaper, we have improved the genetic-algorithm-based k-medoids clustering algorithmand the k-means clustering algorithm,so that the program can determine the number ofclassifications automatically and we get a good result.
引文
(1) 夏德深,傅德胜.现代图像处理技术和应用.东南大学出版社,1997.
    (2) 王耀男.计算机图像处理与识别技术.北京:高等教育出版社,2001.
    (3) KennethR.castleman.数字图像处理.北京:电子工业出版社,2002.
    (4) Gonzalez,R.C.数字图像处理.北京:电子工业出版社,2003.
    (5) E. L. Hall et al.. A Survey of Preprocessing and Feature Extraction Techniques for Radiographic Images. IEEE Trans. Computers, C-20, 9, September 1971, 1032-1044.
    (6) R. A. Hummel. Image Enhancement by Histogram Hyperbolizaton .Compuer Graphics and Image Processing, 1977, 184-195.
    (7) Fisher D. Knowledge acquisition via incremental conceptual clustering Machine Learning, 1987.
    (8) Srinivas M, Patnaik L M. Adaptive Probabilities of Crossover and Mutation in Genetic Algorithm IEEE transactions on Systems,. Manand Cybernetics, 1994.
    (9) 宋光明,宋建设.导弹打击机场跑道的计算机模拟.火力与指挥控制.2001,26(4):67-69.
    (10) 汪民乐.战术导弹对机场攻击作战效能的计算机模拟.火力与指挥控制.1998,23(2):59-62.
    (11) 李新其,卢江仁.系统目标毁伤效果指标建模方法探讨.指挥控制与仿真.2007,29(1):69-73.
    (12) 姚弘毅,郑垣模,崔首东,黄赛超.火炮对目标毁伤仿真模拟方法研究.装备与技术.2006,10:50-52.
    (13) 周娟,熊忠阳,张玉芳,任芳.基于最大最小距离法的多中心聚类算法.计算机应用.2006,26(6):1425-1427.
    (14) 张义良.基于遗传算法的一种自动聚类算法.萍乡高等专科学校学报.2006,3:43-45.
    (15) Babu G P, Murty M N. A near-optimal initial seed value selection in K-means algorithm using a genetic algorithm Pattern Recogn. Lett, 1993.
    (16) 王红睿,赵黎明,裴剑.均衡化的改进K均值聚类法.吉林大学学报.2006,24(2):172-176.
    (17) Karypis G, Han E H, Kumar V. CHAMELEON: A hierarchical clustering algorithm using dynamic modeling Computer, 1999.
    (18) 王汉芝,刘振全.一种新的确定K-均值算法初始聚类中心的方法.天津科技大学学.报 2005,20(4):76-79.
    (19) 张永生,巩丹超.高分辨率遥感卫星应用——成像模型、处理算法及应用技术.北京:科学出版社,2004.
    (20) 卜纳特(Pratt,W.K.).数字图像处理.北京:机械工业出版社,2005.
    (21) 马波,周成平,娄联堂,张天序.基于图像分析的机场打击效果自动评估研究.华中科技大学学报.2004,32(6):13-15.
    (22) 倪林,冷洪超.机场区域变化检测研究.遥感技术应用,2002,17(4):185~192.
    (23) 舒健生,王运吉,朱昱.子母弹抛撒半径对机场毁伤效果影响分析.火力与指挥控制.2001,26(3):49-50.
    (24) 杨静宇,曹雨龙.计算机图像处理及常用算法手册.南京:南京大学出版社,1997.
    (25) Boley D L. Principal direction divisive partitioning Data Mining and Knowledge Discovery, 1998.
    (26) 何斌,马天予,王运坚,朱红莲.Visual C++数字图像处理.北京:人民邮电出版社,2001.
    (27) 陈洁,张迎春,张燕平,张铃.基于信息粒度的聚类分析及其应用.中国图像图形学 报,2007,12(1):87-91.
    (28) 郝占刚,王正欧,基于遗传算法和k-medoids算法的聚类新算法.信息检索技术,2006,5:44-57.
    (29) 王小平,曹立明,遗传算法:理论、应用及软件实现.西安:西安交通大学出版社,2002,,82-131.
    (30) K. Krishna, M. Narasimha Murty. Genetic K-Means Algorithm. IEEE Transactions on systems, man, and cybernetics-partB: Cybernetics, 1999, 29(3): 433-439.
    (31) 王敞,陈增强,袁著祉.基于遗传算法的k均值聚类分析.计算机科学,2003,30(2):163-164.
    (32) 陈纯.计算机图像处理技术与算法.北京:清华大学出版社,2003.
    (33) 罗军辉,冯力等.Matlab 7.0在图像处理中的应用.北京:机械工业出版社,2005.
    (34) 佃袁勇.基于遥感影像的变化检测研究.武汉大学,2005.
    (35) 陈志鹏,邓鹏,种劲松,王宏琦.纹理特征在SAR图像变化检测中的应用.遥感技术与应用.2002,17(3):162-166.
    (36) Fung F, Le Drew E. Application of Principle Components Analysis to Change Detection. Photogrammetric Engineering & Remote Sensing. 1987. 53(12): 1649-1658.
    (37) Merrill K. Ridd A. Comparison of Four Algorithm for Change Detection in An Urban Environment. Remote Sensing of Environment. 1998. 63: 95-100.
    (38) N. R. Pal, J. C. Bezdek, E. C. K. Tsao. Ceneralized clustering networks and Kohonen self-organizing scheme. IEEE Transactions. on Neural Networks, 1993.
    (39) Rignot E. et al. Change Detection Techniques for ERS-1 SAR Data. IEEE Trans. Geosci. Remote Sens., 1993, 31(4): 896.
    (40) 陈富龙,张红,王超.SAR变化检测技术发展综述.遥感技术与应用,2007,22(1):109-115.
    (41) J Holland. Adaptation in Nature and Artificial Systems. Ann Arbor: The University of Michigan Press, 1975.
    (42) [1] Yu S H, Srivastava A, Mehra R K. Automatic battle damage assessment based on laser radar imagery SPIE, 1998.
    (43) 朱近,夏德深,戴奇燕,史栋林,刘莉娜.侵彻子母弹对跑道封锁概率与打击效果评估火力与指挥控制,2007,34(4):106-108.
    (44) Tukey J W. Nonlinear Method for Smoothing Data. Conference Record. New York: Eascon Publisher, 1974. 673.
    (45) 邢延铭.一种基于遗传算法和模糊规则的分类算法.吉林大学学报,2006,27(2):31-35.
    (46) 李正东,郑晓东,雍松林.目标毁伤评判的探讨.光电工程.2002.29(3):17-20.
    (47) 李桂清,李陶深.扫描线种子填充算法的问题及改进.广西大学学报(自然科学版),1998,23(03):207-211.
    (48) Brown L G. A survey of image registration techniques. ACM Computing Surveys, 1992.
    (49) J. Hartian. Clustering Algorithms. Wiley, NewYork, 1975.
    (50) K. Kristinsson end G. A. Dumont. System identification and control using genetic algorithms. IEEE Treru. Syat., Men. Cy6ern., 1992, 22(5), 1033-1046.
    (51) 姜园,张朝阳,仇佩亮,戚玉鹏.对聚类算法普遍存在问题的解决办法.电路与系统学报.2004,9(3):92-98.
    (52) Modha D, Spangler W. Feature weighting in k-means clustering. Machine Learning, 2002, 47.
    (53) 唐立新,杨自厚,王梦光.用遗传算法改进聚类分析中的K-平均算法.数理统计与应用概率,1997,12(4):350-356.
    (54) 刘健庄,谢维信,黄建军,李文化.聚类分析的遗传算法方法.电子学报,1995,23(11):81-83.
    (55) 戴晓晖,李敏强,寇纪淞.基于遗传算法的动态聚类方法.系统工程理论与实践,1999,10:108-116.
    (56) 孙志胜,曹爱增等.基于遗传算法的聚类分析及其应用.济南大学学报.2004,18(2):127-129.

© 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