二维经验模态分解研究及其在图像处理中的应用
|
摘要
二维经验模态分解是将Hilbert-Huang变换向二维信号处理上的一种推广,有可能成为一种全新的二维信号处理方法。二维经验模态分解是一个开放性的问题,其算法本身尚有许多需要完善的地方；而二维经验模态分解的应用研究也是目前图像处理领域里的一个研究热点。
本文首先研究了二维经验模态分解算法的优化问题,在现有几种比较成功的曲面拟合算法的基础上分析了获得正确模态所需要的合理的筛分次数问题,并提出了基于被筛分曲面极值点数量和分布变化规律的筛分停止准则。本文将模态分解中取上下包络均值的过程定义为包络均值运算,进而推导出各个模态的包络均值表示式,分解出了二维模态分解过度筛分之后得到的各个模态图像中异常信息的成分,并分析了这些成分和对应模态之间的跟随关系。根据BEMD的空间滤波特性和过筛分成分与对应模态之间的跟随关系,提出了二维空间域限带信号的包络均值运算的简单数学模型假设,并据此假设对BEMD无穷多次筛分的结果作了猜想。
其后,本文对新准则下获得模态的各方面性质进行了分析。对二维模态的分析主要涉及的几个方面包括：能量,频率,相位和可分离度等等。这样的分析一方面证明了新准则的合理性,另一方面也丰富了二维信号的相位理论,为后续的应用研究提供了理论支持。
在二维经验模态分解的应用研究中,本文根据二维信号的相位理论改进了几种传统的纹理分割方法,并且分析了将二维经验模态分解理论引入到纹理分割中的可能性和应用价值,基于不同纹理分析方法对不同类型纹理具有不同捕捉能力的特点提出了并行叠加的无监督聚类思想；而根据文中前半部分提出的包络均值表示式和对各模态的性质分析,将利用网格特征点表示出来的各个均值曲面分别进行压缩,再根据余量的包络均值表示式将各个均值曲面分别重建后再相加就得到了第一余量曲面(图像)的高质量的还原结果。将余量曲面的压缩结果与Linderhed的VSDCTEMD方法结合,就得到了改进的基于二维经验模态分解的图像压缩方法。
本文提出的算法分别在光学图像和侧扫声纳图像的处理中经过大量的实验,实验证明了文中算法的正确性和可靠性。
The Bidimensional Empirical mode decomposition (BEMD) theory is the extention of the Hilbert-Huang transform to the two-dimensional signal processing, and it would be another successful two-dimensional signal processing approach. The BEMD is an open research, whose primary algorithm is to be perfected, and its application research is also a hotspot in the field of image processing.
This dissertation studies on optimizing the BEMD algorithm firstly. On the basis of several effective surface-fitting algorithms, the reasonable sifting times is analyzed to get the right Intrinsic Mode Function (IMF), and the criterion for stopping the sifting process based on the characteristic points changing rule is brought out. The Empirical mode decomposition course of getting mean envelope is definited as mean envelope operation, so as to deduce the formula to express the IMFs with mean envelopes, the abnormal components existing in the over-sifting IMFs are extracted out, and the follow relationship between these components and their corresponding IMFs is analyzed. According to this follow relationship and the filter bank feature of the BEMD, the hypothesis about the mean envelope operation on the two-dimensional space frequency band limited signal is advised, and according to this hypothesis, the guess about the result of the BEMD infinite sifting is brought out.
For the next step, the IMF's qualities under the new criterion is analyzed, mainly including the energy, the frequency, the phase and the detachable degree, to prove the reasonability of the new criterion on one hand, and to enrich the two-dimensional signal phase theory on the other hand, which will support the application research latterly.
In applications, several classic texture segmentation approaches are modified according to the two-dimensional phase theory, and the possibility and the applied values of taking BEMD into the texture segmentation issue are analyzed. Considering the different effects of the different texture distinguishing instruments, the idea of the side-by-side overlapping unsupervised classification is brought out. According to the mean envelope operation and the quality of the IMF, the several mean surfaces are respectively compressed by representing them with the grid characteristic points, and the high quality reconstruction of the first residue surface (image) is got by adding the several reconstructed mean surfaces together. Combined residue compression with Linderhed's VSDCTEMD approach, the improved image compression approach is achieved.
Several ways to examine the algorithms on the optical or the underwater acoustic images are performed; and the result proves the rightness and reliability of the method in this dissertation.
本文首先研究了二维经验模态分解算法的优化问题,在现有几种比较成功的曲面拟合算法的基础上分析了获得正确模态所需要的合理的筛分次数问题,并提出了基于被筛分曲面极值点数量和分布变化规律的筛分停止准则。本文将模态分解中取上下包络均值的过程定义为包络均值运算,进而推导出各个模态的包络均值表示式,分解出了二维模态分解过度筛分之后得到的各个模态图像中异常信息的成分,并分析了这些成分和对应模态之间的跟随关系。根据BEMD的空间滤波特性和过筛分成分与对应模态之间的跟随关系,提出了二维空间域限带信号的包络均值运算的简单数学模型假设,并据此假设对BEMD无穷多次筛分的结果作了猜想。
其后,本文对新准则下获得模态的各方面性质进行了分析。对二维模态的分析主要涉及的几个方面包括：能量,频率,相位和可分离度等等。这样的分析一方面证明了新准则的合理性,另一方面也丰富了二维信号的相位理论,为后续的应用研究提供了理论支持。
在二维经验模态分解的应用研究中,本文根据二维信号的相位理论改进了几种传统的纹理分割方法,并且分析了将二维经验模态分解理论引入到纹理分割中的可能性和应用价值,基于不同纹理分析方法对不同类型纹理具有不同捕捉能力的特点提出了并行叠加的无监督聚类思想；而根据文中前半部分提出的包络均值表示式和对各模态的性质分析,将利用网格特征点表示出来的各个均值曲面分别进行压缩,再根据余量的包络均值表示式将各个均值曲面分别重建后再相加就得到了第一余量曲面(图像)的高质量的还原结果。将余量曲面的压缩结果与Linderhed的VSDCTEMD方法结合,就得到了改进的基于二维经验模态分解的图像压缩方法。
本文提出的算法分别在光学图像和侧扫声纳图像的处理中经过大量的实验,实验证明了文中算法的正确性和可靠性。
The Bidimensional Empirical mode decomposition (BEMD) theory is the extention of the Hilbert-Huang transform to the two-dimensional signal processing, and it would be another successful two-dimensional signal processing approach. The BEMD is an open research, whose primary algorithm is to be perfected, and its application research is also a hotspot in the field of image processing.
This dissertation studies on optimizing the BEMD algorithm firstly. On the basis of several effective surface-fitting algorithms, the reasonable sifting times is analyzed to get the right Intrinsic Mode Function (IMF), and the criterion for stopping the sifting process based on the characteristic points changing rule is brought out. The Empirical mode decomposition course of getting mean envelope is definited as mean envelope operation, so as to deduce the formula to express the IMFs with mean envelopes, the abnormal components existing in the over-sifting IMFs are extracted out, and the follow relationship between these components and their corresponding IMFs is analyzed. According to this follow relationship and the filter bank feature of the BEMD, the hypothesis about the mean envelope operation on the two-dimensional space frequency band limited signal is advised, and according to this hypothesis, the guess about the result of the BEMD infinite sifting is brought out.
For the next step, the IMF's qualities under the new criterion is analyzed, mainly including the energy, the frequency, the phase and the detachable degree, to prove the reasonability of the new criterion on one hand, and to enrich the two-dimensional signal phase theory on the other hand, which will support the application research latterly.
In applications, several classic texture segmentation approaches are modified according to the two-dimensional phase theory, and the possibility and the applied values of taking BEMD into the texture segmentation issue are analyzed. Considering the different effects of the different texture distinguishing instruments, the idea of the side-by-side overlapping unsupervised classification is brought out. According to the mean envelope operation and the quality of the IMF, the several mean surfaces are respectively compressed by representing them with the grid characteristic points, and the high quality reconstruction of the first residue surface (image) is got by adding the several reconstructed mean surfaces together. Combined residue compression with Linderhed's VSDCTEMD approach, the improved image compression approach is achieved.
Several ways to examine the algorithms on the optical or the underwater acoustic images are performed; and the result proves the rightness and reliability of the method in this dissertation.
引文
[1]L.科恩著.白居宪译.时频分析理论与应用.西安交通大学出版社,1998：1页,32-33页,57-67页
[2]邹红星,周小波,李延达.时频分析回溯与前瞻.电子学报.2000,28(9)：78-84页
[3]钟佑明.希尔波特—黄变换局瞬信号分析理论的研究.重庆大学博士学位论文.2002
[4]Norden E. Huang, Zheng Shen. The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis, Proc. R. Soc. London. A 454,1998:903-995P
[5]Flandrin, P., Rilling, F.& Goncaleves, P.2004 Empirical mode decomposition as a. filter bank. IEEE Signal Process. Lett.11,112-114P
[6]Chen, Q., Norden E. Huang, Riemenschneider, S.& Xu, Y.2006 A B-spline approach for empirical mode decompositions. Adv. Comput. Math. 24,171-195P
[7]杨万利.数值分析教程.国防工业出版社,2002：50-81页
[8]林成森.数值计算方法.科学出版社,1998：122-167页
[9]韩春明,郭华东,王长林.利用经验模态分解方法抑制SAR斑点噪声[J].遥感学报.2002,6(4)：266-271页
[10]沈滨,崔峰,彭思龙.二维EMD的纹理分析和图像瞬时频率估计[J].计算机辅助设计与图形学学报.2005,10(17)：2345-2352页
[11]崔峰.EMD算法与图像时频分析[D]．北京：中国科学院自动化研究所博士学位论文.2005
[12]J. C. Nunes, Y. Bouaoune, E. Delechelle. Texture analysis based on the bidimensional empirical mode decomposition [J]. Mach. Vision App.2003
[13]J. C. Nunes, Y. Bouaoune, E. Delechelle. Image analysis by bidimensional empirical mode decomposition [J]. Image and Vision Computing,2003(21): 1019-1026P
[14]J. C. Nunes, Y. Bouaoune, E. Delechelle. Bidimensional empirical mode decomposition modified for texture analysis[C]. SCIA 2003 13th Scandinavian Conference on Image Analysis, June 29-July 2 2003
[15]J. C. Nunes, S. Guyot, E. Delechelle. Texture analysis based on local analysis of the bidimensional empirical mode decomposition [J]. Machine Vision and Applications,2005 (16):177-188P
[16]宋平舰,张杰.二维经验模分解在海洋遥感图像信息分离中的应用[J].高技术通讯.2001,9：62-67页
[17]秦勃,时鹏.经验模式多尺度图像分解[J].工程图学学报.2002,4：73-78页
[18]刘忠轩,彭思龙.方向EMD分解与其在纹理分割中的应用[J].中国科学E辑信息科学.2005,35(2)：113-123页
[19]Christophe Damerval. A fast algorithm for bidimensional EMD [J]. Signal Processing Letters, IEEE,2005,12(10):701-704P
[20]Y. Xu, B. Liu, J. Liu and S. Riemenschneider, "Two-dimensional empirical mode decomposition by finite elements", Proceedings of the Royal Society London A, doi:10.1098/repa.2006.1700
[21]Watson, D.1981 computing the n-dimensional Delaunay tessellation with applications to Voronoi polytopes. Comput. J.24,167-172P
[22]Sapidis, N.& Perucchio, K.1991 Delaunay triangulation of arbitrarily shaped domains. Comput. Aided Geom. Des.8,421-437P
[23]Ciarlet, P. G.1976 Numerical analysis of the finite element method, Seminaire de Mathematiques Superieures, No.59. Montreal:Les Presses de l' Universite de Montreal
[24]邓拥军.EMD方法及Hilbert变化中边界问题的处理[J].科学通报.2001,46(3)：257-263页
[25]张郁山,梁建文.应用自回归模型处理EMD方法中的边界问题[J].自然科学进展.2003
[26]黄大吉,赵进平.希尔伯特-黄变化的端点延拓[J].海洋学报.2003,1：1-11页
[27]余泊.自适应时频分析方法及其在故障诊断中的应用[D].大连：‘大连理工大学博士学位论文.1998
[28]盖强.局域波时频分析方法的理论研究与应用[D].大连：大连理工大学博士学位论文.2001
[29]C. Damerval, S. Meignen and V. Perrier, "A fast algorithm for bidimensional EMD", IEEE Signal Processing Letters, Vol.12, No.10, Oct.2005, pp. 701-704P
[30]Anna Linderhed, "2D empirical mode decomposition in the spirit of image compression", SPIE Proceedings Vol.4738, Wavelet and Independent Component Analysis Applications IX, Orlando, FL 2002, April 2002:1-8P
[31]Z. Liu and S. Peng, "Boundary processing of bidimensional EMD using texture synthesis", IEEE Signal Processing Letters, Vol.12, No.1, Jan. 2005:33-36P
[32]Bell B.M., Percival D.B. A two-step Burg algorithm. IEEE Transactions on Signal Processing,1991,39(1):185-189P
[33]Norden E. Huang, Zheng. Shen, and Steven. R. Long.A New View of Nonliear water waves:the Hilbert Spectrum. Annual Review of Fluid Mechanics,1999:417-457P
[34]Rilling G, Flandrin P, Goncalves P. On Emprical cal Mode Decomposition and its algorithms [C]. IEEE EURASIP Workshop on Nonlinear Signal and Image Processing, Grado (I), June,2003:56-59P
[35]郑天翔,杨力华.经验模式分解算法的探讨和改进[J].中山大学学报(自然科学版).2007,46(1)：12-16页
[36]Cheng Junsheng, Yu Dejie, Yang Yu, "Research on the intrinsic mode function (IMF) criterion in EMD method ", Mechanical Systems and Signal Processing Vol.20, No.2006:817-824P
[37]B. Xuan, Q. Xie and S. Peng, "EMD sifting based on bandwidth", IEEE Signal Processing Letters, Vol.14, No.8, Aug.2007:537-540P
[38]Bulow T.and Sommer G. Hypercomplex signals-a novel extension of the analytic signal to the multidimensional case. IEEE Trans.on Signal
Processing,2001,49 (11):2844-2855P
[39]徐冠雷,王孝通,徐晓刚.二象Hilbert变换[J].自然科学进展.2007,17(8)：1120-1129页
[40]Bulow T., Hypercomplex Spectral Signal Representations for the Processing and Analysis of Images [D]. Kiel, Germany:Christian Albrechts University,1999
[41]崔峰,曹学光,彭思龙.新的四元数解析信号相位定义.中国图象图形学报.2006,11(2)：251-258页
[42]S. L. Hahn. Multidimensional complex signals with single-orthant spectra. Proc. IEEE,80(8):1287-1300P
[43]S. L. Hahn. Hilbert Transforms in Signal Processing. Artech House, Boston, London,1996
[44]L. Haglund. Adaptive Multidimensional Filtering. PhD thesis, Link"oping University,1992
[45]Felsberg M. Signal processing using frequency domain methods in Clifford algebra. Master's thesis, University of Kiel,1998
[46]Felsberg M. and Sommer G., "Structure multivector for local analysis of images," Inst. Comput. Sci. Appl. Math, Christian-Albrechts-Univ. Kiel, Kiel, Germany, Tech. Rep.2001, Feb.20
[47]Felsberg, M., Sommer, G.:The monogenic signal. IEEE Transactions on Signal Processing 49 (2001) 3136-3144P
[48]程军圣,于德介,杨宇.基于EMD的能量算子解调方法及其在机械故障诊断中的应用[J].机械工程学报.2004,40(8)：115-118页
[49]程军圣,于德介,杨宇.经典模态分解方法中内禀函数判据问题研究[J].中国机械工程.2004,15(20)：1861-1864页
[50]于德介,杨宇,程军圣.一种基于EMD和SVM的齿轮故障诊断方法[J].机械工程学报.2005,41(1)：140-144页
[51]胡劲松,杨世锡.旋转机械振动信号基于EMD的HT和Winger分布时频分析比较.汽轮机技术.2003,45(5)：307-309页
[52]杨世锡,胡劲松.旋转机械振动信号基于EMD的希尔伯特变换和小波
变换时频分析比较.中国电机工程学报.2003,23(6)：102-107页
[53]蒋济同.海洋平台的模态参数识别和损伤诊断研究[D].青岛海洋大学博士学位论文.2003
[54]Hui-Fang Chen. Heart Rate Variability Analysis of Orthostatic Fainting in Spinal Cord Injury Treatment by Hilbert Huang Transform. Master's Thesis of the National University of Singapore.2004
[55]M.E. Montesinosa. Hilbert-Huang analysis of BWR neutron detector signals:application to DR calculation and corrupted signal analysis. Annals of Nuclear Energy,2003:715-727P
[56]Abhijeet Dipak Shinde.A Wavelet Packet Based Sifting Process and Its Application for Structural Health Monitoring. Master's Thesis of WORCESTER POLYTECHNIC INSTITUTE,2004
[57]Yang, J.N., Lin, S., and Pan, S.. Damage Identification of Structures Using Hilbert Huang Spectral Analysis. CD ROM,8 pages, Proc.15th ASCE Engineering Mechanics Conference, Columbia University, New York, NY, 2002
[58]Ray Ruichong Zhang. Hilbert-Huang Transform Analysis of Dynamic and Earthquake Motion Recordings. JOURNAL OF ENGINEERING MECHANICS (?) ASCE,2003:861-875P
[59]Charles-Alexandre Zimmermann and Richard Seymour, F.ASCE. Detection of Breaking in a Deep Water Wave Record. JOURNAL OF WATERWAY, PORT, COASTAL AND OCEAN ENGINEERING,2002:72-78P
[60]徐冠雷,王孝通,徐晓刚,朱涛.基于限邻域EMD的图像增强[J].电子学报.2006,34(9)：1635-1639页
[61]X. Qin, S. Liu, Z. Wu and J. Han, "Medical image enhancement method based on 2D empirical mode decomposition", the 2nd international conference on Bioinformatics and Biomedical Engineering,16-18 May, 2008:2533-2536P
[62]R. Bhagavatula and M. Savvides, "Analyzing facial images using empirical mode decomposition for illumination artifact removal and improved face
recognition", ICASSP 2007, Vol.1,505-508P
[63]L. He and H. Wang, "Spatial-variant image filtering based on bidimensional empirical mode decomposition",18th international conference on Pattern Recognition,2006, ICPR 2006, Vol.2,1196-1199P
[64]J. Lee, P. Huang, C. Chiang, T-M Tu and C. Chang, "An empirical mode decomposition approach for iris recognition", international conference on Image Processing,2006, ICIP 2006:289-292P
[65]杨志华,齐东旭,杨力华,吴立军.基于经验模式分解的汉字字体识别方法[J].软件学报.2005,16(8)：1438-1444页
[66]Anna. Linderhed, "Adaptive image compression with wavelet packets and empirical mode decomposition", PhD dissertation, Linkoping University, Sweden,2004
[67]Jalil Taghia, M. A. Doostari and Jalal Taghia, "An image watermarking method based on bidimensional empirical mode decomposition", Congress on image and signal processing,2008 (CISP '08) Vol.5,27-30 May 2008: 674-678P
[68]Su P., Kuo C., Stegangraphy in JPEG2000 compressed images. IEEE Transaction on Consumer Electronics,2003,49(4):824-832P
[69]谭舜泉,黄继武,杨志华.基于Hilbert-Huang变换的JPEG2000隐写分析[J].计算机学报.2006,29(9)：1702-1710页
[70]Y. Tian, Y. Huang and Y. Li, "Image zooming method using 2D EMD technique", Proceedings of 6th world congress on intelligent control and automation,21-23 Jun,2006, China,10036-10040P
[71]S. Sinclair. Empirical mode decomposition in 2-D space and time:a tool for space-time rainfall analysis and nowcasting[C]. Hydrol. Earth Syst. Sci. Discuss.2005,2:289-318P
[72]Riemenschneider, S., Liu, B., Xu, Y.& Huang, N.2005 B-spline based empirical mode decomposition. In Hilbert-Huang transform:introduction and applications, ch 2 (ed. N. Huang& S. Shen),27-55. Singapore:World Scientic
[73]Chen, Q., Huang, N. E., Riemenschneider, S.& Xu, Y.2006 A B-spline approach for empirical mode decompositions. Adv. Comput. Math.24, 171-195P
[74]Riemenschneider, S., Liu, B., Xu, Y.& Huang, N.2005 B-spline based empirical mode decomposition. In Hilbert-Huang transform:Introduction and applications, ch 2 (ed. N. Huang& S. Shen),27-55. Singapore:World Scientic
[75]Ciarlet, P. G.1976 Numerical analysis of the finite element method, Seminaire de Mathematiques Superieures, No.59. Montreal:Les Presses de 1'Universite de Montreal
[76]F. L. Bookstein, "Principal Warps:Thin-Plate Splines and the Decomposition of Deformations." IEEE Transactions on Pattern Analysis and Machine Intelligence,1989,11(6):567-585P
[77]J. Meinguet, "Surface spline interpolation:Basic theory and computational aspects." Approximation Theory and Spline Functions,127-142, Dordrecht, 1984
[78]Norden E. Huang, Wu Man-Li C., Long S. R. A confidence limit for the empirical mode decomposition and Hilbert spectral analysis [J], Proc. R. Soc. Lond.2003, A (459):2317-2345P
[79]宋立新,王祁,王玉静.具有间断事件检测和分离的经验模态分解方法[J].哈尔滨工程大学学报.2007；28(2)：178-182页
[80]何振亚.多维数字图像处理技术.北京国防工业出版社,1995
[81]A.V奥本海姆,R.W.谢弗著,董士嘉译.数字信号处理.科学出版社
[82]Rafael C.Gonzalez.数字图像处理(第二版).电子工业出版社,2007.8：213-215页
[83]朱华,黄辉宁,李永庆,梅文博.随机信号分析.北京理工大学出版社,1990.12：75页,199-202页
[84]Fortuna L, Muscato G, Xibilia M.G A hypercomplex positioning.1996 IEEE Internationals ymposium on 609-612 neural network platform for robot Circuits and Systems,1996,3
[85]Chen Ming-Yang, Li Hua-Chieh, Pei Soo-Chang. Algebraic identification for optimal nonorthogonality spltimes complexs pace-time block codes using tensor product on quate mions. IEEE Transactionson Information Theory,2005,51(1):32-33P
[86]Bulow T., Sommer, G Quatemionic Gabor filters for local structure classification. Fourteenth International Conference on Patern Recognition, 1998,1:808-810P
[87]Bulow T., Sommer, G.A novel approach to the 2nd analytic signal. International Conference on Computer Analysis of Images and Paterns.19 99,1:25-32P
[88]Haralick R M, Statistical and Structural Approaches to Texture[J], Proc. IEEE,1979,67:786-804P
[89]薄华,马缚龙,焦李成,图像纹理的灰度共生矩阵计算问题的分析[J].电子学报.2006,34(1)：155-158页
[90]N.A buja, A. Rosenfeld. Mosaic models for textures. IEEE Trans. Pattern Analysis. Machine Intelligence,1981,3:1-10P
[91]R.C. Dubes, A.K. Jain. Random field models in image analysis. Journal of Application Statistic,1989,16:131-164P
[92]R.M.H aralick. Statistical and structural approaches to texture. IEEE Proceeding,1979,67:786-804P
[93]M.Tuceryan, A.K.Jain.Texture analysis. Handkook of pattern recognation and computer vision,1993,2:35-276P
[94]H.Wechsler.Texture analysis-a survey. Signal process,1980,2:27-28P
[95]郑南宁.计算机视觉与模式识别[M].北京：国防工业出版社,1998：89-96页
[96]J.C. Dunn.A fuzzy relative of the ISODATA process and its use in detecting compact, well-separated clusters. J. Cybern,1974,3:32-57P
[97]R. L. Cannon. J. Dave and J. C. Bezdek. Efficient implementation of the fuzzyc-means clustering algorithms. IEEE Trans,1986:PAMI-8 (2): 248-255P
[98]Bezdek J C. Pattern Recognition with Fuzzy Objective Function Algorithms [J]. New York:Plenum,1981
[99]王晓丹.基于模糊聚类及神经网络的纹理分割方法研究[D].西安：西北工业大学博士学位文.2002：69-82页
[100]Jain A.K., Farrokhnia F. Unsupervised texture segmentation using Gabor filters. Pattern Recognition,1991,24 (12):1167-1186P
[101]Pollen D A, Ronner S E. Visual conical neurons as localized spatial frequency filters[J]. IEEE Transactions on System Man and Cybernetics, 1983,13(5):907-916P
[102]章毓晋.图像处理和分析[M].北京：清华大学出版社,1999：297-300页
[103]Bulow T., Sommer, G Quaternionic Gabor filters for local structure classification. Fourteenth International Conference on Patter n Recognition, 1998,1:808-810P
[104]Bovik.A.C. Clark Marianna. Multichannel texture analysis using localized spatial IEEE Trans. on Pattern Analysis and Machine Intelligence,1990,12 (1):55-73P
[105]武震.基于分形理论的图像分割.南京航空航天大学,2002：29-31页
[106]刘卓夫,桑恩方.基于分形理论的声纳图像识别.微机发展.2004.14(4)：55-57页
[107]B.B. Chaudhuri, N.Sarkar.Texture segmentation through fractal dimensions. IEEE Trans. PAMI.1995,17(1):72-77P
[108]N.Sarkar, B.B. Chaudhuri. An efficient approach to estimate fractal dimension of textural images. Pattern Recognition.1992 25 (9):1035-1041P
[109]贾云得.机器视觉[M].北京：科学出版社,2000.82-105页
[110]Rousson M, Brox T, Deriche R. Active unsupervised texture segmentation on diffusion based feature space. In:Dyer C, ed. Proc. of the 2003 IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, Madison:IEEE Computer Society,2003. Vol 2.:699-704P
[111]James C, Bezdek, Nikhil R, Pal. Cluster validation with general-ized dunn's index 1 The 2nd New Zealand International Two-Stream Confl Artificial Neural Networks and Expert Systems, Dunedin, New Zealand, 1995
[112]I. Gath, A B Geva. Unsupervised optimal fuzzy clustering. IEEE Trans. Pattern Analysis and Machine Intelligence,1989,11 (7):773-781P
[113]X. L. Xie, G. Beni. A validity measure for fuzzy clustering. IEEE Trans. Pattern Analysis and Machine Intelligence,1991,13 (8):841-847P
[114]Mahamadou Idrissa, Marc Acheroy. Texture classification using Gabor filters. Pattern Recognition Letters,2002,23 (9):1095-1102P
[115]蒋晓悦,赵荣椿,江泽涛.基于FCM的无监督纹理分割[J].计算机研究与发展.2005.12(5)：862-867页
[116]Luo J.B, Savakis A.E. Self-supervised texture segmentation using complementary types of features. Pattern Recognition,2001,34 (11):29 71-298P
[117]A. Linderhed, "Variable Sampling of the Empirical Mode Decomposition of Two-Dimensional Signals", International Journal of Wavelets, Multiresolution and Information Processing (IJWMIP) special issue on Sampling Problems Related to Wavelet Theory and Time-Frequency Analysis Sept.2005 vol.3, no.3:435-452P
[118]Kobbelt, L., Campagna, S., Vorsatz, J.& Seidel, H.-P.1998 Interactive multiresolution modeling on arbitrary meshes. Proc. SIGGRAPH, New York:ACM Press. Vol.98:105-114P
[119]Riemenschneider, S., Liu, B., Xu, Y.& Huang, N.2005 B-spline based empirical mode decomposition. In Hilbert-Huang transform:introduction and applications, ch 2 (ed. N. Huang& S. Shen), pp.27-55. Singapore: World Scientic
[120]A. Linderhed, "Image compression based on empirical mode decomposition". Uppsala, Proceedings of SSBA symposium on image analysis, SSBA'04, March 2004:110-113P
[121]刘晨晨.高分辨率成像声纳图像识别技术研究[D].哈尔滨：哈尔滨工 程大学博士学位文.2006：60-89页
[122]郭海涛.高分辨率成像声呐后置图像处理[D].哈尔滨：哈尔滨工程大学博士学位文.2002：74-82页
[123]梁开龙.海洋测绘与海战地理环境信息保障.测绘工程.2001,10(1)：11-13页
[124]刘宝华,丁继胜,裴延良等.海洋地球物理探测技术及其在近海工程中的应用.海洋科学进展.2005,23(3)：374-384页
[125]张增喆.二维经验模态分解在声纳图像压缩中的应用[D].哈尔滨： 哈尔滨工程大学硕士学位文.2009：36-46页
[126]卢迎春,桑恩方.基于主动声纳的水下目标特征提取技术综述.哈尔滨工程大学学报.1997,18(6)：43-54页
[2]邹红星,周小波,李延达.时频分析回溯与前瞻.电子学报.2000,28(9)：78-84页
[3]钟佑明.希尔波特—黄变换局瞬信号分析理论的研究.重庆大学博士学位论文.2002
[4]Norden E. Huang, Zheng Shen. The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis, Proc. R. Soc. London. A 454,1998:903-995P
[5]Flandrin, P., Rilling, F.& Goncaleves, P.2004 Empirical mode decomposition as a. filter bank. IEEE Signal Process. Lett.11,112-114P
[6]Chen, Q., Norden E. Huang, Riemenschneider, S.& Xu, Y.2006 A B-spline approach for empirical mode decompositions. Adv. Comput. Math. 24,171-195P
[7]杨万利.数值分析教程.国防工业出版社,2002：50-81页
[8]林成森.数值计算方法.科学出版社,1998：122-167页
[9]韩春明,郭华东,王长林.利用经验模态分解方法抑制SAR斑点噪声[J].遥感学报.2002,6(4)：266-271页
[10]沈滨,崔峰,彭思龙.二维EMD的纹理分析和图像瞬时频率估计[J].计算机辅助设计与图形学学报.2005,10(17)：2345-2352页
[11]崔峰.EMD算法与图像时频分析[D]．北京：中国科学院自动化研究所博士学位论文.2005
[12]J. C. Nunes, Y. Bouaoune, E. Delechelle. Texture analysis based on the bidimensional empirical mode decomposition [J]. Mach. Vision App.2003
[13]J. C. Nunes, Y. Bouaoune, E. Delechelle. Image analysis by bidimensional empirical mode decomposition [J]. Image and Vision Computing,2003(21): 1019-1026P
[14]J. C. Nunes, Y. Bouaoune, E. Delechelle. Bidimensional empirical mode decomposition modified for texture analysis[C]. SCIA 2003 13th Scandinavian Conference on Image Analysis, June 29-July 2 2003
[15]J. C. Nunes, S. Guyot, E. Delechelle. Texture analysis based on local analysis of the bidimensional empirical mode decomposition [J]. Machine Vision and Applications,2005 (16):177-188P
[16]宋平舰,张杰.二维经验模分解在海洋遥感图像信息分离中的应用[J].高技术通讯.2001,9：62-67页
[17]秦勃,时鹏.经验模式多尺度图像分解[J].工程图学学报.2002,4：73-78页
[18]刘忠轩,彭思龙.方向EMD分解与其在纹理分割中的应用[J].中国科学E辑信息科学.2005,35(2)：113-123页
[19]Christophe Damerval. A fast algorithm for bidimensional EMD [J]. Signal Processing Letters, IEEE,2005,12(10):701-704P
[20]Y. Xu, B. Liu, J. Liu and S. Riemenschneider, "Two-dimensional empirical mode decomposition by finite elements", Proceedings of the Royal Society London A, doi:10.1098/repa.2006.1700
[21]Watson, D.1981 computing the n-dimensional Delaunay tessellation with applications to Voronoi polytopes. Comput. J.24,167-172P
[22]Sapidis, N.& Perucchio, K.1991 Delaunay triangulation of arbitrarily shaped domains. Comput. Aided Geom. Des.8,421-437P
[23]Ciarlet, P. G.1976 Numerical analysis of the finite element method, Seminaire de Mathematiques Superieures, No.59. Montreal:Les Presses de l' Universite de Montreal
[24]邓拥军.EMD方法及Hilbert变化中边界问题的处理[J].科学通报.2001,46(3)：257-263页
[25]张郁山,梁建文.应用自回归模型处理EMD方法中的边界问题[J].自然科学进展.2003
[26]黄大吉,赵进平.希尔伯特-黄变化的端点延拓[J].海洋学报.2003,1：1-11页
[27]余泊.自适应时频分析方法及其在故障诊断中的应用[D].大连：‘大连理工大学博士学位论文.1998
[28]盖强.局域波时频分析方法的理论研究与应用[D].大连：大连理工大学博士学位论文.2001
[29]C. Damerval, S. Meignen and V. Perrier, "A fast algorithm for bidimensional EMD", IEEE Signal Processing Letters, Vol.12, No.10, Oct.2005, pp. 701-704P
[30]Anna Linderhed, "2D empirical mode decomposition in the spirit of image compression", SPIE Proceedings Vol.4738, Wavelet and Independent Component Analysis Applications IX, Orlando, FL 2002, April 2002:1-8P
[31]Z. Liu and S. Peng, "Boundary processing of bidimensional EMD using texture synthesis", IEEE Signal Processing Letters, Vol.12, No.1, Jan. 2005:33-36P
[32]Bell B.M., Percival D.B. A two-step Burg algorithm. IEEE Transactions on Signal Processing,1991,39(1):185-189P
[33]Norden E. Huang, Zheng. Shen, and Steven. R. Long.A New View of Nonliear water waves:the Hilbert Spectrum. Annual Review of Fluid Mechanics,1999:417-457P
[34]Rilling G, Flandrin P, Goncalves P. On Emprical cal Mode Decomposition and its algorithms [C]. IEEE EURASIP Workshop on Nonlinear Signal and Image Processing, Grado (I), June,2003:56-59P
[35]郑天翔,杨力华.经验模式分解算法的探讨和改进[J].中山大学学报(自然科学版).2007,46(1)：12-16页
[36]Cheng Junsheng, Yu Dejie, Yang Yu, "Research on the intrinsic mode function (IMF) criterion in EMD method ", Mechanical Systems and Signal Processing Vol.20, No.2006:817-824P
[37]B. Xuan, Q. Xie and S. Peng, "EMD sifting based on bandwidth", IEEE Signal Processing Letters, Vol.14, No.8, Aug.2007:537-540P
[38]Bulow T.and Sommer G. Hypercomplex signals-a novel extension of the analytic signal to the multidimensional case. IEEE Trans.on Signal
Processing,2001,49 (11):2844-2855P
[39]徐冠雷,王孝通,徐晓刚.二象Hilbert变换[J].自然科学进展.2007,17(8)：1120-1129页
[40]Bulow T., Hypercomplex Spectral Signal Representations for the Processing and Analysis of Images [D]. Kiel, Germany:Christian Albrechts University,1999
[41]崔峰,曹学光,彭思龙.新的四元数解析信号相位定义.中国图象图形学报.2006,11(2)：251-258页
[42]S. L. Hahn. Multidimensional complex signals with single-orthant spectra. Proc. IEEE,80(8):1287-1300P
[43]S. L. Hahn. Hilbert Transforms in Signal Processing. Artech House, Boston, London,1996
[44]L. Haglund. Adaptive Multidimensional Filtering. PhD thesis, Link"oping University,1992
[45]Felsberg M. Signal processing using frequency domain methods in Clifford algebra. Master's thesis, University of Kiel,1998
[46]Felsberg M. and Sommer G., "Structure multivector for local analysis of images," Inst. Comput. Sci. Appl. Math, Christian-Albrechts-Univ. Kiel, Kiel, Germany, Tech. Rep.2001, Feb.20
[47]Felsberg, M., Sommer, G.:The monogenic signal. IEEE Transactions on Signal Processing 49 (2001) 3136-3144P
[48]程军圣,于德介,杨宇.基于EMD的能量算子解调方法及其在机械故障诊断中的应用[J].机械工程学报.2004,40(8)：115-118页
[49]程军圣,于德介,杨宇.经典模态分解方法中内禀函数判据问题研究[J].中国机械工程.2004,15(20)：1861-1864页
[50]于德介,杨宇,程军圣.一种基于EMD和SVM的齿轮故障诊断方法[J].机械工程学报.2005,41(1)：140-144页
[51]胡劲松,杨世锡.旋转机械振动信号基于EMD的HT和Winger分布时频分析比较.汽轮机技术.2003,45(5)：307-309页
[52]杨世锡,胡劲松.旋转机械振动信号基于EMD的希尔伯特变换和小波
变换时频分析比较.中国电机工程学报.2003,23(6)：102-107页
[53]蒋济同.海洋平台的模态参数识别和损伤诊断研究[D].青岛海洋大学博士学位论文.2003
[54]Hui-Fang Chen. Heart Rate Variability Analysis of Orthostatic Fainting in Spinal Cord Injury Treatment by Hilbert Huang Transform. Master's Thesis of the National University of Singapore.2004
[55]M.E. Montesinosa. Hilbert-Huang analysis of BWR neutron detector signals:application to DR calculation and corrupted signal analysis. Annals of Nuclear Energy,2003:715-727P
[56]Abhijeet Dipak Shinde.A Wavelet Packet Based Sifting Process and Its Application for Structural Health Monitoring. Master's Thesis of WORCESTER POLYTECHNIC INSTITUTE,2004
[57]Yang, J.N., Lin, S., and Pan, S.. Damage Identification of Structures Using Hilbert Huang Spectral Analysis. CD ROM,8 pages, Proc.15th ASCE Engineering Mechanics Conference, Columbia University, New York, NY, 2002
[58]Ray Ruichong Zhang. Hilbert-Huang Transform Analysis of Dynamic and Earthquake Motion Recordings. JOURNAL OF ENGINEERING MECHANICS (?) ASCE,2003:861-875P
[59]Charles-Alexandre Zimmermann and Richard Seymour, F.ASCE. Detection of Breaking in a Deep Water Wave Record. JOURNAL OF WATERWAY, PORT, COASTAL AND OCEAN ENGINEERING,2002:72-78P
[60]徐冠雷,王孝通,徐晓刚,朱涛.基于限邻域EMD的图像增强[J].电子学报.2006,34(9)：1635-1639页
[61]X. Qin, S. Liu, Z. Wu and J. Han, "Medical image enhancement method based on 2D empirical mode decomposition", the 2nd international conference on Bioinformatics and Biomedical Engineering,16-18 May, 2008:2533-2536P
[62]R. Bhagavatula and M. Savvides, "Analyzing facial images using empirical mode decomposition for illumination artifact removal and improved face
recognition", ICASSP 2007, Vol.1,505-508P
[63]L. He and H. Wang, "Spatial-variant image filtering based on bidimensional empirical mode decomposition",18th international conference on Pattern Recognition,2006, ICPR 2006, Vol.2,1196-1199P
[64]J. Lee, P. Huang, C. Chiang, T-M Tu and C. Chang, "An empirical mode decomposition approach for iris recognition", international conference on Image Processing,2006, ICIP 2006:289-292P
[65]杨志华,齐东旭,杨力华,吴立军.基于经验模式分解的汉字字体识别方法[J].软件学报.2005,16(8)：1438-1444页
[66]Anna. Linderhed, "Adaptive image compression with wavelet packets and empirical mode decomposition", PhD dissertation, Linkoping University, Sweden,2004
[67]Jalil Taghia, M. A. Doostari and Jalal Taghia, "An image watermarking method based on bidimensional empirical mode decomposition", Congress on image and signal processing,2008 (CISP '08) Vol.5,27-30 May 2008: 674-678P
[68]Su P., Kuo C., Stegangraphy in JPEG2000 compressed images. IEEE Transaction on Consumer Electronics,2003,49(4):824-832P
[69]谭舜泉,黄继武,杨志华.基于Hilbert-Huang变换的JPEG2000隐写分析[J].计算机学报.2006,29(9)：1702-1710页
[70]Y. Tian, Y. Huang and Y. Li, "Image zooming method using 2D EMD technique", Proceedings of 6th world congress on intelligent control and automation,21-23 Jun,2006, China,10036-10040P
[71]S. Sinclair. Empirical mode decomposition in 2-D space and time:a tool for space-time rainfall analysis and nowcasting[C]. Hydrol. Earth Syst. Sci. Discuss.2005,2:289-318P
[72]Riemenschneider, S., Liu, B., Xu, Y.& Huang, N.2005 B-spline based empirical mode decomposition. In Hilbert-Huang transform:introduction and applications, ch 2 (ed. N. Huang& S. Shen),27-55. Singapore:World Scientic
[73]Chen, Q., Huang, N. E., Riemenschneider, S.& Xu, Y.2006 A B-spline approach for empirical mode decompositions. Adv. Comput. Math.24, 171-195P
[74]Riemenschneider, S., Liu, B., Xu, Y.& Huang, N.2005 B-spline based empirical mode decomposition. In Hilbert-Huang transform:Introduction and applications, ch 2 (ed. N. Huang& S. Shen),27-55. Singapore:World Scientic
[75]Ciarlet, P. G.1976 Numerical analysis of the finite element method, Seminaire de Mathematiques Superieures, No.59. Montreal:Les Presses de 1'Universite de Montreal
[76]F. L. Bookstein, "Principal Warps:Thin-Plate Splines and the Decomposition of Deformations." IEEE Transactions on Pattern Analysis and Machine Intelligence,1989,11(6):567-585P
[77]J. Meinguet, "Surface spline interpolation:Basic theory and computational aspects." Approximation Theory and Spline Functions,127-142, Dordrecht, 1984
[78]Norden E. Huang, Wu Man-Li C., Long S. R. A confidence limit for the empirical mode decomposition and Hilbert spectral analysis [J], Proc. R. Soc. Lond.2003, A (459):2317-2345P
[79]宋立新,王祁,王玉静.具有间断事件检测和分离的经验模态分解方法[J].哈尔滨工程大学学报.2007；28(2)：178-182页
[80]何振亚.多维数字图像处理技术.北京国防工业出版社,1995
[81]A.V奥本海姆,R.W.谢弗著,董士嘉译.数字信号处理.科学出版社
[82]Rafael C.Gonzalez.数字图像处理(第二版).电子工业出版社,2007.8：213-215页
[83]朱华,黄辉宁,李永庆,梅文博.随机信号分析.北京理工大学出版社,1990.12：75页,199-202页
[84]Fortuna L, Muscato G, Xibilia M.G A hypercomplex positioning.1996 IEEE Internationals ymposium on 609-612 neural network platform for robot Circuits and Systems,1996,3
[85]Chen Ming-Yang, Li Hua-Chieh, Pei Soo-Chang. Algebraic identification for optimal nonorthogonality spltimes complexs pace-time block codes using tensor product on quate mions. IEEE Transactionson Information Theory,2005,51(1):32-33P
[86]Bulow T., Sommer, G Quatemionic Gabor filters for local structure classification. Fourteenth International Conference on Patern Recognition, 1998,1:808-810P
[87]Bulow T., Sommer, G.A novel approach to the 2nd analytic signal. International Conference on Computer Analysis of Images and Paterns.19 99,1:25-32P
[88]Haralick R M, Statistical and Structural Approaches to Texture[J], Proc. IEEE,1979,67:786-804P
[89]薄华,马缚龙,焦李成,图像纹理的灰度共生矩阵计算问题的分析[J].电子学报.2006,34(1)：155-158页
[90]N.A buja, A. Rosenfeld. Mosaic models for textures. IEEE Trans. Pattern Analysis. Machine Intelligence,1981,3:1-10P
[91]R.C. Dubes, A.K. Jain. Random field models in image analysis. Journal of Application Statistic,1989,16:131-164P
[92]R.M.H aralick. Statistical and structural approaches to texture. IEEE Proceeding,1979,67:786-804P
[93]M.Tuceryan, A.K.Jain.Texture analysis. Handkook of pattern recognation and computer vision,1993,2:35-276P
[94]H.Wechsler.Texture analysis-a survey. Signal process,1980,2:27-28P
[95]郑南宁.计算机视觉与模式识别[M].北京：国防工业出版社,1998：89-96页
[96]J.C. Dunn.A fuzzy relative of the ISODATA process and its use in detecting compact, well-separated clusters. J. Cybern,1974,3:32-57P
[97]R. L. Cannon. J. Dave and J. C. Bezdek. Efficient implementation of the fuzzyc-means clustering algorithms. IEEE Trans,1986:PAMI-8 (2): 248-255P
[98]Bezdek J C. Pattern Recognition with Fuzzy Objective Function Algorithms [J]. New York:Plenum,1981
[99]王晓丹.基于模糊聚类及神经网络的纹理分割方法研究[D].西安：西北工业大学博士学位文.2002：69-82页
[100]Jain A.K., Farrokhnia F. Unsupervised texture segmentation using Gabor filters. Pattern Recognition,1991,24 (12):1167-1186P
[101]Pollen D A, Ronner S E. Visual conical neurons as localized spatial frequency filters[J]. IEEE Transactions on System Man and Cybernetics, 1983,13(5):907-916P
[102]章毓晋.图像处理和分析[M].北京：清华大学出版社,1999：297-300页
[103]Bulow T., Sommer, G Quaternionic Gabor filters for local structure classification. Fourteenth International Conference on Patter n Recognition, 1998,1:808-810P
[104]Bovik.A.C. Clark Marianna. Multichannel texture analysis using localized spatial IEEE Trans. on Pattern Analysis and Machine Intelligence,1990,12 (1):55-73P
[105]武震.基于分形理论的图像分割.南京航空航天大学,2002：29-31页
[106]刘卓夫,桑恩方.基于分形理论的声纳图像识别.微机发展.2004.14(4)：55-57页
[107]B.B. Chaudhuri, N.Sarkar.Texture segmentation through fractal dimensions. IEEE Trans. PAMI.1995,17(1):72-77P
[108]N.Sarkar, B.B. Chaudhuri. An efficient approach to estimate fractal dimension of textural images. Pattern Recognition.1992 25 (9):1035-1041P
[109]贾云得.机器视觉[M].北京：科学出版社,2000.82-105页
[110]Rousson M, Brox T, Deriche R. Active unsupervised texture segmentation on diffusion based feature space. In:Dyer C, ed. Proc. of the 2003 IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, Madison:IEEE Computer Society,2003. Vol 2.:699-704P
[111]James C, Bezdek, Nikhil R, Pal. Cluster validation with general-ized dunn's index 1 The 2nd New Zealand International Two-Stream Confl Artificial Neural Networks and Expert Systems, Dunedin, New Zealand, 1995
[112]I. Gath, A B Geva. Unsupervised optimal fuzzy clustering. IEEE Trans. Pattern Analysis and Machine Intelligence,1989,11 (7):773-781P
[113]X. L. Xie, G. Beni. A validity measure for fuzzy clustering. IEEE Trans. Pattern Analysis and Machine Intelligence,1991,13 (8):841-847P
[114]Mahamadou Idrissa, Marc Acheroy. Texture classification using Gabor filters. Pattern Recognition Letters,2002,23 (9):1095-1102P
[115]蒋晓悦,赵荣椿,江泽涛.基于FCM的无监督纹理分割[J].计算机研究与发展.2005.12(5)：862-867页
[116]Luo J.B, Savakis A.E. Self-supervised texture segmentation using complementary types of features. Pattern Recognition,2001,34 (11):29 71-298P
[117]A. Linderhed, "Variable Sampling of the Empirical Mode Decomposition of Two-Dimensional Signals", International Journal of Wavelets, Multiresolution and Information Processing (IJWMIP) special issue on Sampling Problems Related to Wavelet Theory and Time-Frequency Analysis Sept.2005 vol.3, no.3:435-452P
[118]Kobbelt, L., Campagna, S., Vorsatz, J.& Seidel, H.-P.1998 Interactive multiresolution modeling on arbitrary meshes. Proc. SIGGRAPH, New York:ACM Press. Vol.98:105-114P
[119]Riemenschneider, S., Liu, B., Xu, Y.& Huang, N.2005 B-spline based empirical mode decomposition. In Hilbert-Huang transform:introduction and applications, ch 2 (ed. N. Huang& S. Shen), pp.27-55. Singapore: World Scientic
[120]A. Linderhed, "Image compression based on empirical mode decomposition". Uppsala, Proceedings of SSBA symposium on image analysis, SSBA'04, March 2004:110-113P
[121]刘晨晨.高分辨率成像声纳图像识别技术研究[D].哈尔滨：哈尔滨工 程大学博士学位文.2006：60-89页
[122]郭海涛.高分辨率成像声呐后置图像处理[D].哈尔滨：哈尔滨工程大学博士学位文.2002：74-82页
[123]梁开龙.海洋测绘与海战地理环境信息保障.测绘工程.2001,10(1)：11-13页
[124]刘宝华,丁继胜,裴延良等.海洋地球物理探测技术及其在近海工程中的应用.海洋科学进展.2005,23(3)：374-384页
[125]张增喆.二维经验模态分解在声纳图像压缩中的应用[D].哈尔滨： 哈尔滨工程大学硕士学位文.2009：36-46页
[126]卢迎春,桑恩方.基于主动声纳的水下目标特征提取技术综述.哈尔滨工程大学学报.1997,18(6)：43-54页
© 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 |