基于DICOM标准的医学图像压缩技术研究
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摘要
随着医学影像设备如超声、放射、CT等大量进入医院,数字医学影像数据的广泛应用,PACS(Picture Archiving & Communication System)系统应运而生。它是一种用于医学图像采集、存储、管理和传输的图像存档及通信系统(Picture Archiving & Communication System,PACS)。在PACS系统中运行的医学图像必须有统一的标准,美国放射学院和国家电气制造商协会共同制定了DICOM(Imaging and Communication in Medicine)标准,即医学数字成像与通信标准,包括医学的数字成像和通信传输两个方面,成为现在PACS系统中通用的图像标准。医学图像数字量大,对存储设备和传输设备的性能都提出了极大的挑战。因此,对于医学图像压缩算法的研究非常必要。
本文基于医学图像的DICOM格式、提升小波变换和BP网络算法原理,结合临床实践的可操作性,对医学图像压缩算法进行了较为深入的研究和探讨。论文的主要工作如下:
(1)论文在提升小波变换的基础上,研究了一种新的有效的图像压缩算法。它使用系数为有理数的9/7提升小波滤波器,同时融合了BP神经网络和人眼视觉系统。为了提高重建图像的精确性,本文算法采用改进的系数为有理数的滤波器,解决了小波变换后的系数为浮点数造成的压缩过程不可逆的问题;进一步的,在提升小波变换基础上,针对其滤波器系数进行了大量实验,最终选取到一组有理系数,在数值上接近原来的无理系数,在压缩性能上与原滤波器相差无几。
(2)小波变换后根据人眼视觉系统的原理,对小波系数进行按分解级划分,根据频带的重要性选择不同BP网络进行自组织学习压缩。同时,针对BP网络中不同的训练算法进行多组仿真实验和对比,通过得到的仿真结果选取了最优的算法,为后续章节中软件系统的开发打下了基础。
(3)基于Windows环境,采用Visual C++可视化编程开发了医学图像压缩软件系统。主要完成本文所提出算法和经典EZW编码压缩算法以及DICOM文件与BMP文件的转换。可以通过可视化拉条来选择图像压缩质量,在当前窗口下观察到不同PSNR值情况时的图像质量来决定最终的压缩比。
(4)开发了DICOM文件操作软件。DICOM文件作为一种运行在PACS系统中的特殊的文件格式,有其独特的文件头和数据格式构成方法,在普通电脑Windows系统中不能浏览;同时,一般医学图像像素深度差别大,正常显示范围经常不能包含其全部信息,因此,本文在详细介绍DICOM文件格式的基础上,实现了从DICOM文件格式到位图文件格式的转换以及把窗口区域的图像数据线性的转换到显示器的最大显示范围内,动态调整窗宽和窗位,观察医学图像全部信息,进而使对DICOM文件的浏览不止局限于PACS系统工作站中,而可以在任何一台普通电脑上进行。
As a great number of medical image equipments,such as ultrasonic instruments,radiation and CT,have entered hospitals,digital medical image data have been widely used and the PACS emerged.PACS is a kind of picture archiving and communication system(Picture Archiving & Communication System,PACS)for medical image sampling,storing,administration and transmission.So the medical images in PACS must abide by uniform standards. American radiation institute and national electrical manufactures association established the DICOM(Digital Imaging and Communication in Medicine) standard,i.e,medical digital imaging and communication standard which consists of medical digital imaging and communication transmission.And this has become the general images standard in PACS now.The quantity of medical images is so large that it is a great chalienge to the performance of the storage equipments and the transmission equipments.On the premise of not affecting the clinic diagnosis,it is quite necessary to compress the medical images.
Combining with clinic operability,this paper does deep research and discussion on medical images compression algorithm on the basis of DICOM formation of medical images,lifting integer wavelet and neural network algorithm.The main work of this paper is as follows
(1)This paper mainly focuses on a new kind of image compression algorithm,which takes advantage of a 9/7 lifting wavelet filter with rational coefficients and combines BP neural network and human vision system,on the basis of lifting wavelet transformation.To improve the quality of reconstructed image,the algorithm in this paper adopts improved filter with rational coefficients,and it overcomes the irreversibility of the compression process caused by float coefficients.After wavelet transformation,the wavelet coefficients are blocked by frequency band and imported to BP network to do self-organizing learning compression.Then the validity of different reconstructed images via different BP networks algorithms was discussed and the optimal algorithm was chosen by simulation.Due to the preprocessing,the wavelet coefficients of which the numerical value is in close agreement and the energy is concentrated,which would benefit network learning.At last,the reconstructed image is of good vision effect and better peak signal to noise ratio(PSNR),and the algorithm is easy to operate.
(2)Using Visual C++ visual programming technology,medical images software compression system in windows operation system is developed.It mainly achieves the algorithm proposed in this paper, the classical EZW coding compression method and the transformation between DICOM and BMP files.Users can choose different image compression quality with visual scroll bar,and can decide the final compression ratio via previewing images of different PSNR value.
(3)A DICOM files operating software is developed.As a DICOM file includes unique file head and data format,it can't be browsed in general computer.Meanwhile,medical images are of great difference in pixels depth,so the normal displaying range always can only reflect parts of the information included by the images.Therefore, this paper gives a method to transform the DICOM files to bitmap files format,and linearly transform the images data in the windows area into the largest displaying area of the display,and adapt the width and position of the window,in order to observe all information of the medical image.This method makes it possible to browse the DICOM file in any common computer
本文基于医学图像的DICOM格式、提升小波变换和BP网络算法原理,结合临床实践的可操作性,对医学图像压缩算法进行了较为深入的研究和探讨。论文的主要工作如下:
(1)论文在提升小波变换的基础上,研究了一种新的有效的图像压缩算法。它使用系数为有理数的9/7提升小波滤波器,同时融合了BP神经网络和人眼视觉系统。为了提高重建图像的精确性,本文算法采用改进的系数为有理数的滤波器,解决了小波变换后的系数为浮点数造成的压缩过程不可逆的问题;进一步的,在提升小波变换基础上,针对其滤波器系数进行了大量实验,最终选取到一组有理系数,在数值上接近原来的无理系数,在压缩性能上与原滤波器相差无几。
(2)小波变换后根据人眼视觉系统的原理,对小波系数进行按分解级划分,根据频带的重要性选择不同BP网络进行自组织学习压缩。同时,针对BP网络中不同的训练算法进行多组仿真实验和对比,通过得到的仿真结果选取了最优的算法,为后续章节中软件系统的开发打下了基础。
(3)基于Windows环境,采用Visual C++可视化编程开发了医学图像压缩软件系统。主要完成本文所提出算法和经典EZW编码压缩算法以及DICOM文件与BMP文件的转换。可以通过可视化拉条来选择图像压缩质量,在当前窗口下观察到不同PSNR值情况时的图像质量来决定最终的压缩比。
(4)开发了DICOM文件操作软件。DICOM文件作为一种运行在PACS系统中的特殊的文件格式,有其独特的文件头和数据格式构成方法,在普通电脑Windows系统中不能浏览;同时,一般医学图像像素深度差别大,正常显示范围经常不能包含其全部信息,因此,本文在详细介绍DICOM文件格式的基础上,实现了从DICOM文件格式到位图文件格式的转换以及把窗口区域的图像数据线性的转换到显示器的最大显示范围内,动态调整窗宽和窗位,观察医学图像全部信息,进而使对DICOM文件的浏览不止局限于PACS系统工作站中,而可以在任何一台普通电脑上进行。
As a great number of medical image equipments,such as ultrasonic instruments,radiation and CT,have entered hospitals,digital medical image data have been widely used and the PACS emerged.PACS is a kind of picture archiving and communication system(Picture Archiving & Communication System,PACS)for medical image sampling,storing,administration and transmission.So the medical images in PACS must abide by uniform standards. American radiation institute and national electrical manufactures association established the DICOM(Digital Imaging and Communication in Medicine) standard,i.e,medical digital imaging and communication standard which consists of medical digital imaging and communication transmission.And this has become the general images standard in PACS now.The quantity of medical images is so large that it is a great chalienge to the performance of the storage equipments and the transmission equipments.On the premise of not affecting the clinic diagnosis,it is quite necessary to compress the medical images.
Combining with clinic operability,this paper does deep research and discussion on medical images compression algorithm on the basis of DICOM formation of medical images,lifting integer wavelet and neural network algorithm.The main work of this paper is as follows
(1)This paper mainly focuses on a new kind of image compression algorithm,which takes advantage of a 9/7 lifting wavelet filter with rational coefficients and combines BP neural network and human vision system,on the basis of lifting wavelet transformation.To improve the quality of reconstructed image,the algorithm in this paper adopts improved filter with rational coefficients,and it overcomes the irreversibility of the compression process caused by float coefficients.After wavelet transformation,the wavelet coefficients are blocked by frequency band and imported to BP network to do self-organizing learning compression.Then the validity of different reconstructed images via different BP networks algorithms was discussed and the optimal algorithm was chosen by simulation.Due to the preprocessing,the wavelet coefficients of which the numerical value is in close agreement and the energy is concentrated,which would benefit network learning.At last,the reconstructed image is of good vision effect and better peak signal to noise ratio(PSNR),and the algorithm is easy to operate.
(2)Using Visual C++ visual programming technology,medical images software compression system in windows operation system is developed.It mainly achieves the algorithm proposed in this paper, the classical EZW coding compression method and the transformation between DICOM and BMP files.Users can choose different image compression quality with visual scroll bar,and can decide the final compression ratio via previewing images of different PSNR value.
(3)A DICOM files operating software is developed.As a DICOM file includes unique file head and data format,it can't be browsed in general computer.Meanwhile,medical images are of great difference in pixels depth,so the normal displaying range always can only reflect parts of the information included by the images.Therefore, this paper gives a method to transform the DICOM files to bitmap files format,and linearly transform the images data in the windows area into the largest displaying area of the display,and adapt the width and position of the window,in order to observe all information of the medical image.This method makes it possible to browse the DICOM file in any common computer
引文
[1]熊宇,段会龙,吕维雪.图像归档和通讯系统(PACS)的发展与应用[J].国外医学:生物医学工程分册,2000.23(2):70-75
[2]王保华,罗立民.生物医学电子学[M].南京:东南大学出版社,2001.3
[3]Kunt,Murat,Ikonomopoulos,Athanassios.SECOND-GENERATION IMAGE CODING TECHNIQUES[J].Proceeding of the IEEE,1985,73(4):549-574.
[4]Macovski Albert.Medical Imaging System.[M].Englewood Cliffs,New Jersey:Prentice-Hall,Inc.,1983
[5]刘政凯等.数字图像恢复与重建[M].合肥:中国科技大学出版社,1989
[6]沈兰荪.图像编码与异步传输[M].北京:人民邮电出版社,1998
[7]Villasenor,J,Belzer,B,Liao,J.Wavelet Filter Evaluation for Image Compression[J],IEEE Transaction on Image Processing,1995,Vol.2:1053-1060
[8]Huang H K.PACS basic Principles and Applications[M].Wiley-Liss Inc,1999
[9]林天毅,段会龙,吕维雪.医学数字图像通讯.DICOM标准及在我国的实施策略.国外医学.生物医学工程分册1998,Vol.21,No.2:65-73.
[10]Huang H K.PACS picture archiving and communication system in biomedical & imaging[M].VCH Publishers Inc,1996
[11]http://www.dicom.org/
[12]JPEG 2000 part Ⅰ final draft international standard[S].ISO/IEC JTC1/SC29/WG1 N1890,2000.
[13]National Electrical Manufacturers Association.Digital Imaging and Communications in Medicine(DICOM)[S].PS3.3-1999.
[14]吕晓东.医学数字影像通讯(DICOM)标准及其应用[J].医疗卫生装备,2001(25):143-144.
[15]王志远,余厚军,石明国.医学图像通讯标准DICOM原理与应用(一)[J].现代医用影像学.2000.Vol.9.No.2:84-87.
[16]王志远,余厚军,石明国.医学图像通讯标准DICOM原理与应用(二)[J]. 现代医用影像学,2000.Vol.9 No.3 134-137.
[17]王志远,余厚军,石明国.医学图像通讯标准DICOM原理与应用(三)[J].现代医用影像学,2000.Vol.9.No.4:177-179.
[18]谢长生,熊华明,陈颉.DICOM图象显示的研究与实现[J].计算机工程与科学,2002,Vol.19.No.6
[19]余海英.DICOM数据集与DCM文件格式[J].计算机应用,2001,(8)
[20]何斌,金永杰.DICOM医学图像文件格式.世界医疗器械[J],2001.1,7(1):14-19
[21]胡阳秋,高小榕,高上凯.医学图像DICOM格式转换软件的设计与实现[J].北京生物医学工程,2000,19(4):193-197.
[22]NE BA,CLEARY K R,NORTON G S,et al Challenges encounted while Plementing a multi-endor teleradiology network using DICOM3.0 SPIE proceedings[C]//Medical Imaging 1997:PACS Design and Evaluation Engineering and Clinical Issue 1997,237-245
[23]夏德深,傅德胜.计算机图像处理及应用[M].南京:东南大学出版社,2004
[24]张尤赛,陈福民.医学图像窗口变换的加速算法[J].计算机工程与应用,2003,(13):218-220.
[25]彭玉华.小波变换与工程应用[M].北京:科学出版社,1999
[26]Mallat S G.A theory for multiresolution signal decomposition:The Wavelet representation[M].IEEE Trans.And Machine Intell.,1989,PAMI-11:674-693
[27]Mallat S G Multifrequency channel decompositions of images and wavelet models[J].IEEE Trans.Acoust,Speech,Signal Processing,1989,ASSP37:2091-2110.
[28]Mallat S G.multiresolution approximations and wavelet orthonormal bases of L~2(R)[J].Trans Amer Math.Soc.1989(315):69-87
[29]陈书海,傅录祥.实用数字图像处理[M].北京:科学技术出版社,2005
[30]成礼智等.小波的理论与应用[M].北京:科学技术出版社,2004
[31]Liang Xuezhang,He Jiaxing,Wang Xinming etc.Wavelet Analysis[M].Beijing:National Defence Industry Press,2005.(in China)
[32]DAUBECHIES SWELDENS W.Factoring Wavelet Transforms into lifting steps[J].Journal of Fourie Analysis applications.1984,4(3):245-267.
[33]W.Sweldens,Lossless image compression using integer to integer wavelet transforms[J],International Conference on Image Processing.1997.1(1).pp.596-599
[34]Sweldens W.The lifting scheme:A construction of second generation wavelets [J].SIAM Journal on Mathematical Analysis,Volume 29 Issue 2:Pages 511-546
[35]Calderbank A R,Daubechies I,Sweldens W,et al.Lossless image compression using integer to integer wavelet transforms[C].International Conference on Image Processing(ICIP).1997.596-599.
[36]Calderbank A R,Daubechies I D,Sweldens W,et al.Wavelet transforms that map integers to integers[J].Applied and Computational Harmonic Analysis (ACHA),1998.5(3):332-369.
[37]Dqubechies I,Sweldens W.Factoring Wavelet Transform into Lifting Steps[J].Journal of Fourier Analysis and Applications,1998,4(3):245-267.
[38]Ding Guiguang,Guo Baolong,Wang Yong.A kind of Lifting 9-7-tap Wavelet Filter for Hardware Implementation[J].JOURNAL OF XIDIAN UNIVERSITY,2003,30(10):603-606,622.
[39]JPEG 2000 Part Ⅰ Final Draft International Standard[S].ISO/IECJECI/SC29/WGINI855.2000.08
[40]胡昌华等.基于MATLAB的系统分析与设计-小波分析[M].西安:西安电子科技大学出版社,1999
[41]S.N.Efstratiadis et al.Hierarchical partition priority wavelet image Compression[J].IEEE Trans.Image Processing,1996,5(7):1111-1123
[42]SHAPRIO J M.Embeded image coding using zerotree of wavelet coefficients[J].IEEE Transaction on Signal Processing.1993,41(12):3445-3462
[43]A Said,W A Peaelman.A New Fast and Efficient Image Coded Based On Set Paetitioning in Hierarchical Trees[J].IEEE Trans Circuits and System for Video Technology,1996;(6):243-249
[44]Creusere C D New method of robust image compressing based on the embedded zero tree wavelet algorithm[J].IEEE Trans on Image Processing,1997,6(10):1436-1446
[45]Zhu Xiangjun,Zhu Shan'an.Pliyayefu.A Summary on Wavelet-transform-based Embedded Image Coding Algorithms[J].Signal Processing,2004,20(1):54-58.
[46]R.A.DeVore et al.Image compression through wavelet transform coding[J].IEEE Trans.Image Processing,1996,5(4):719-745
[47]S Carrato.Neural networks for image compression[M].Neural Networks:Advances And Applications 2 ed,Gelenbe Pub,North -Holland,Amaterdam,1992:177-198.
[48]Jinhua Xu,Daniel W.C.A basis selection algorithm for wavelet neural networks[J].Neuro Computing,48:681-689,2002
[49]M Mougeot,R Azencott,B Angeniol Image compression with back propagation improve of the visual restoration using different cost functions[J].Neural Networks,1991,4(4):467 -476.
[50]B.Widrow and M.A.Lehr,30 years of adaptive neural networks:perception,madaline and backpropagation[J],Proc.IEEE,Vol.8,No.9,Sept.1990,pp 1415-1441.
[51]Martin THagan,Howard B Demuth,MarkH Beale著.戴盔等译.神经网络设计[M].北京:机械工业出版社,2002.9 239-243.
[52]D.E.Rumelhart,G.E.Hinton,and R.J.Williams,learning internal representations by error propagation,Parallel distributed processing[M],Vol.1,pp.318-362,Cambridge,MA:M.I.T.Press,1986.
[53]S.Roy and John J.Shynk,Analysis of the momentum LMS algorithm[J],IEEE Trans.Acoust.,Speech,Signal Processing,Vol.ASSP-38,pp.2088-2098,Dec.1990.
[54]B.Widrow,J.M.Mcmool,M.G.Larimore,and C.R.Johnson,Jr.,Stationary and nonstationary learning characteristics of LMS adaptive filter[J].Proc.IEEE vol.64,pp.1157-1162,1976.
[55]李珊珊,康志伟,何怡刚.高性能的9/7小波滤波器组设[J].Vol.28,No.10,2007.5:2361-2363
[56]刘桂红,孙春义.对JPEG2000的CDF9/7滤波器的改进[J].中国科技信息,2007年第16期:64-65
[57]Kotteri K A,Bell A E,Carletta J E.Design of multiplierless,high-performance,wavelet filter banks with image compression application[J].IEEE Tran on Circuits and systems,2004,51(3):483-494.
[2]王保华,罗立民.生物医学电子学[M].南京:东南大学出版社,2001.3
[3]Kunt,Murat,Ikonomopoulos,Athanassios.SECOND-GENERATION IMAGE CODING TECHNIQUES[J].Proceeding of the IEEE,1985,73(4):549-574.
[4]Macovski Albert.Medical Imaging System.[M].Englewood Cliffs,New Jersey:Prentice-Hall,Inc.,1983
[5]刘政凯等.数字图像恢复与重建[M].合肥:中国科技大学出版社,1989
[6]沈兰荪.图像编码与异步传输[M].北京:人民邮电出版社,1998
[7]Villasenor,J,Belzer,B,Liao,J.Wavelet Filter Evaluation for Image Compression[J],IEEE Transaction on Image Processing,1995,Vol.2:1053-1060
[8]Huang H K.PACS basic Principles and Applications[M].Wiley-Liss Inc,1999
[9]林天毅,段会龙,吕维雪.医学数字图像通讯.DICOM标准及在我国的实施策略.国外医学.生物医学工程分册1998,Vol.21,No.2:65-73.
[10]Huang H K.PACS picture archiving and communication system in biomedical & imaging[M].VCH Publishers Inc,1996
[11]http://www.dicom.org/
[12]JPEG 2000 part Ⅰ final draft international standard[S].ISO/IEC JTC1/SC29/WG1 N1890,2000.
[13]National Electrical Manufacturers Association.Digital Imaging and Communications in Medicine(DICOM)[S].PS3.3-1999.
[14]吕晓东.医学数字影像通讯(DICOM)标准及其应用[J].医疗卫生装备,2001(25):143-144.
[15]王志远,余厚军,石明国.医学图像通讯标准DICOM原理与应用(一)[J].现代医用影像学.2000.Vol.9.No.2:84-87.
[16]王志远,余厚军,石明国.医学图像通讯标准DICOM原理与应用(二)[J]. 现代医用影像学,2000.Vol.9 No.3 134-137.
[17]王志远,余厚军,石明国.医学图像通讯标准DICOM原理与应用(三)[J].现代医用影像学,2000.Vol.9.No.4:177-179.
[18]谢长生,熊华明,陈颉.DICOM图象显示的研究与实现[J].计算机工程与科学,2002,Vol.19.No.6
[19]余海英.DICOM数据集与DCM文件格式[J].计算机应用,2001,(8)
[20]何斌,金永杰.DICOM医学图像文件格式.世界医疗器械[J],2001.1,7(1):14-19
[21]胡阳秋,高小榕,高上凯.医学图像DICOM格式转换软件的设计与实现[J].北京生物医学工程,2000,19(4):193-197.
[22]NE BA,CLEARY K R,NORTON G S,et al Challenges encounted while Plementing a multi-endor teleradiology network using DICOM3.0 SPIE proceedings[C]//Medical Imaging 1997:PACS Design and Evaluation Engineering and Clinical Issue 1997,237-245
[23]夏德深,傅德胜.计算机图像处理及应用[M].南京:东南大学出版社,2004
[24]张尤赛,陈福民.医学图像窗口变换的加速算法[J].计算机工程与应用,2003,(13):218-220.
[25]彭玉华.小波变换与工程应用[M].北京:科学出版社,1999
[26]Mallat S G.A theory for multiresolution signal decomposition:The Wavelet representation[M].IEEE Trans.And Machine Intell.,1989,PAMI-11:674-693
[27]Mallat S G Multifrequency channel decompositions of images and wavelet models[J].IEEE Trans.Acoust,Speech,Signal Processing,1989,ASSP37:2091-2110.
[28]Mallat S G.multiresolution approximations and wavelet orthonormal bases of L~2(R)[J].Trans Amer Math.Soc.1989(315):69-87
[29]陈书海,傅录祥.实用数字图像处理[M].北京:科学技术出版社,2005
[30]成礼智等.小波的理论与应用[M].北京:科学技术出版社,2004
[31]Liang Xuezhang,He Jiaxing,Wang Xinming etc.Wavelet Analysis[M].Beijing:National Defence Industry Press,2005.(in China)
[32]DAUBECHIES SWELDENS W.Factoring Wavelet Transforms into lifting steps[J].Journal of Fourie Analysis applications.1984,4(3):245-267.
[33]W.Sweldens,Lossless image compression using integer to integer wavelet transforms[J],International Conference on Image Processing.1997.1(1).pp.596-599
[34]Sweldens W.The lifting scheme:A construction of second generation wavelets [J].SIAM Journal on Mathematical Analysis,Volume 29 Issue 2:Pages 511-546
[35]Calderbank A R,Daubechies I,Sweldens W,et al.Lossless image compression using integer to integer wavelet transforms[C].International Conference on Image Processing(ICIP).1997.596-599.
[36]Calderbank A R,Daubechies I D,Sweldens W,et al.Wavelet transforms that map integers to integers[J].Applied and Computational Harmonic Analysis (ACHA),1998.5(3):332-369.
[37]Dqubechies I,Sweldens W.Factoring Wavelet Transform into Lifting Steps[J].Journal of Fourier Analysis and Applications,1998,4(3):245-267.
[38]Ding Guiguang,Guo Baolong,Wang Yong.A kind of Lifting 9-7-tap Wavelet Filter for Hardware Implementation[J].JOURNAL OF XIDIAN UNIVERSITY,2003,30(10):603-606,622.
[39]JPEG 2000 Part Ⅰ Final Draft International Standard[S].ISO/IECJECI/SC29/WGINI855.2000.08
[40]胡昌华等.基于MATLAB的系统分析与设计-小波分析[M].西安:西安电子科技大学出版社,1999
[41]S.N.Efstratiadis et al.Hierarchical partition priority wavelet image Compression[J].IEEE Trans.Image Processing,1996,5(7):1111-1123
[42]SHAPRIO J M.Embeded image coding using zerotree of wavelet coefficients[J].IEEE Transaction on Signal Processing.1993,41(12):3445-3462
[43]A Said,W A Peaelman.A New Fast and Efficient Image Coded Based On Set Paetitioning in Hierarchical Trees[J].IEEE Trans Circuits and System for Video Technology,1996;(6):243-249
[44]Creusere C D New method of robust image compressing based on the embedded zero tree wavelet algorithm[J].IEEE Trans on Image Processing,1997,6(10):1436-1446
[45]Zhu Xiangjun,Zhu Shan'an.Pliyayefu.A Summary on Wavelet-transform-based Embedded Image Coding Algorithms[J].Signal Processing,2004,20(1):54-58.
[46]R.A.DeVore et al.Image compression through wavelet transform coding[J].IEEE Trans.Image Processing,1996,5(4):719-745
[47]S Carrato.Neural networks for image compression[M].Neural Networks:Advances And Applications 2 ed,Gelenbe Pub,North -Holland,Amaterdam,1992:177-198.
[48]Jinhua Xu,Daniel W.C.A basis selection algorithm for wavelet neural networks[J].Neuro Computing,48:681-689,2002
[49]M Mougeot,R Azencott,B Angeniol Image compression with back propagation improve of the visual restoration using different cost functions[J].Neural Networks,1991,4(4):467 -476.
[50]B.Widrow and M.A.Lehr,30 years of adaptive neural networks:perception,madaline and backpropagation[J],Proc.IEEE,Vol.8,No.9,Sept.1990,pp 1415-1441.
[51]Martin THagan,Howard B Demuth,MarkH Beale著.戴盔等译.神经网络设计[M].北京:机械工业出版社,2002.9 239-243.
[52]D.E.Rumelhart,G.E.Hinton,and R.J.Williams,learning internal representations by error propagation,Parallel distributed processing[M],Vol.1,pp.318-362,Cambridge,MA:M.I.T.Press,1986.
[53]S.Roy and John J.Shynk,Analysis of the momentum LMS algorithm[J],IEEE Trans.Acoust.,Speech,Signal Processing,Vol.ASSP-38,pp.2088-2098,Dec.1990.
[54]B.Widrow,J.M.Mcmool,M.G.Larimore,and C.R.Johnson,Jr.,Stationary and nonstationary learning characteristics of LMS adaptive filter[J].Proc.IEEE vol.64,pp.1157-1162,1976.
[55]李珊珊,康志伟,何怡刚.高性能的9/7小波滤波器组设[J].Vol.28,No.10,2007.5:2361-2363
[56]刘桂红,孙春义.对JPEG2000的CDF9/7滤波器的改进[J].中国科技信息,2007年第16期:64-65
[57]Kotteri K A,Bell A E,Carletta J E.Design of multiplierless,high-performance,wavelet filter banks with image compression application[J].IEEE Tran on Circuits and systems,2004,51(3):483-494.