基于小波分析的地形多分辨率建模方法

王江云; 曾琼; 王会霞

doi:10.13700/j.bh.1001-5965.2013.0473

基于小波分析的地形多分辨率建模方法

doi: 10.13700/j.bh.1001-5965.2013.0473

1. 北京航空航天大学自动化科学与电气工程学院, 北京 100191;
2. 北京航天自动控制研究所, 北京 100854

基金项目:

国家自然科学基金资助项目（61174148）

详细信息

作者简介:
王江云（1972-），女，河北定州人，副教授，wangjiangyun@buaa.edu.cn.

中图分类号: TP391
计量
- 文章访问数: 1365
- HTML全文浏览量: 30
- PDF下载量: 587
- 被引次数: 0
出版历程
- 收稿日期: 2013-08-08
- 网络出版日期: 2014-08-20

Multi-resolution modeling of terrain based on wavelet analysis

1. School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
2. Beijing Aerospace Automatic Control Research Institute, Beijing 100854, China

摘要

摘要: 以提高运算效率和存储效率为目的研究了基于小波的数字高程模型（DEM，Digital Elevation Model）数据的多分辨率建模，根据DEM的数据特点在Mallat多分辨率分析算法的基础上，提出了基于小波分析的DEM数据多分辨率建模算法，对算法实现过程中的小波函数以及边界延拓方式的选取进行了阐述，提出了评价建模精度的相关指标，并通过仿真实验确定了恰当的小波参数.仿真结果表明，小波分析法是实现DEM多分辨率建模的有效方法，同时保证了良好的运算效率和存储效率.该方法可应用于地形的快速可视化、飞行器的动态和静态航路规划等工程应用中.
- 建模与仿真 /
- 数字高程模型 /
- 数字地形模型 /
- 多分辨率建模 /
- 小波分析
Abstract: Through wavelet analysis of signal, multi-resolution modeling of digital elevation model (DEM) for the purpose of improving operational efficiency and storage efficiency was studied. According to the characteristics of DEM, on the base of Mallat's multi-resolution analysis (MRA) algorithm, a method for multi-resolution modeling based on wavelet analysis was presented. Then the principles for choosing the fittest wavelet function and boundary extension mode were analyzed. Also a way and several corresponding indexes on evaluating the accuracy of modeling were given. Through simulations, the best wavelet transform parameters were found. Simulation results show that wavelet analysis can be an effective way to achieve DEM data's multi-resolution modeling while operational efficiency and storage efficiency can both be guaranteed. This method can be applied to various engineering such as terrain's quick visualization and aircraft's dynamic or static path planning.
- modeling and simulation /
- digital evaluation model /
- digital terrain model /
- multi-resolution modeling /
- wavelet analysis

HTML全文

参考文献(18)

[1]	Moore I D, Grayson R B,Ladson A R.Digital terrain modelling:a review of hydrological,geomorphological,and biological applications[J].Hydrological Processes,1991,5(1):3-30
[2]	Weibel R, Heller M.Digital terrain modelling[M].Oxford:Oxford University Press,1993
[3]	Wang G X, Zhang,Y B,Li J.Research and practice of accuracy evaluation method in DEM[J].Science of Surveying and Mapping,2006,31(3):73-75
[4]	Torrence C, Compo G P.A practical guide to wavelet analysis[J].Bulletin of the American Meteorological Society,1998, 79(1): 61-78
[5]	Wu J, Amaratunga K.Wavelet triangulated irregular networks[J].International Journal of Geographical Information Science,2003,17(3):273-289
[6]	Burrus C S, Gopinath R A,Guo Haitao,et al.Introduction to wavelets and wavelet transforms:a primer[M].Upper Saddle River:Prentice Hall,1998
[7]	Torrence C, Compo G P.A practical guide to wavelet analysis[J].Bulletin of the American Meteorological Society,1998, 79(1): 61-78
[8]	Daubechies I. The wavelet transform,time-frequency localization and signal analysis[J].IEEE Transactions on Information Theory,1990,36(5):961-1005
[9]	黄为,魏迎梅,宋汉辰,等. 基于小波分析的 DEM 数据多分辨率表达研究[J].计算机仿真,2010,27(5):80-83 Huang Wei,Wei Yingmei,Song Hanchen,et al.Multi-resolution representation of DEM based on wavelet analysis[J].Journal of Computer Simulation,2010,27(5):80-83 (in Chinese)
[10]	Yang J S, Zhou L P.Iterative algorithm of wavelet moments method based on the multi-resolution analysis characteristics of wavelet[C]//2011 2nd IEEE International Conference on Microwave Technology and Computational Electromagnetics.Piscataway,NJ:IEEE,2011:462-465
[11]	Gaouda A M, Salama M M A,Sultan M R,et al.Power quality detection and classification using wavelet-multiresolution signal decomposition[J].IEEE Transactions on Power Delivery,1999,14(4):1469-1476
[12]	Mallat S. A wavelet tour of signal processing[M].Salt Lake City:Academic Press,1999
[13]	Mallat S G. A theory for multiresolution signal decomposition:the wavelet representation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1989,11(7):674-693
[14]	Danovaro E, De Floriani L,Papaleo L,et al.A multi-resolution representation for terrain morphology[C]//Geographic Information Science.Berlin Heidelberg:Springer,2006:33-46
[15]	Danovaro E, De Floriani L,Magillo P,et al.Morphology-driven simplification and multiresolution modeling of terrains[C]//Proceedings of the 11th ACM International Symposium on Advances in Geographic Information Systems.New York:ACM,2003:63-70
[16]	袁礼海,宋建社. 小波变换中的信号边界延拓方法研究[J].计算机应用研究,2006,23(3):25-27 Yuan Lihai,Song Jianshe.Research on signal extended methods in wavelet transform[J].Application Research of Computers,2006,23(3):25-27(in Chinese)
[17]	Herley C. Boundary filters for finite-length signals and time-varying filter banks[J].IEEE Transactions on Circuits and Systems Ⅱ:Analog and Digital Signal Processing,1995,42(2):102-114
[18]	Kharitonenko I, Zhang X,Twelves S.A wavelet transform with point-symmetric extension at tile boundaries[J].IEEE Transactions on Image Processing,2002,11(12):1357-1364