基于小波的雷达图像压缩编码的研究
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摘要
随着我国海上交通运输业的发展,海上事故也有所增多,船舶航行记录仪可以记录包括图像声音等信息的航行数据,为故障排除及事故调查提供依据。在航行数据的存储中船载雷达图像占了较大一部分存储空间,故在传输和存储的过程中,如何在节约存储容量的基础上对雷达图像进行压缩,并达到好的压缩效果,是一个亟需解决的关键问题。由于目前大部分船舶航行记录仪中雷达图像压缩均采用MPEG标准,但该方法没有充分考虑到雷达图像的特征,因此,有必要对雷达图像压缩技术进行新的研究。
本文根据雷达图像的特征以及小波变换在图像压缩方面的成功应用,提出了利用提升小波变换和SPIHT算法与算术编码相结合的方法对雷达图像进行压缩,并将此方法与其他算法的压缩速度和压缩图像效果进行比较。选取不同小波基和分解层数会对图像的压缩性能造成影响,所以小波变换在雷达图像压缩的应用中,小波函数以及分解层数的选择是必须解决的问题。本文根据大量的文献资料,归纳出小波函数的数字特性对图像压缩性能的影响,并以此为依据,选取几种具有代表性的小波函数以及自然图像和雷达图像,通过实验,比较其压缩比和图像的峰值信噪比,最后,选择出较为理想的小波函数和分解层数,为实际应用提供了参考。
文章还对比分析了基于小波变换的图像压缩的经典算法：EZW和SPIHT算法,对两算法的压缩速度与重构图像效果进行比较,从实验结果可以看出SPIHT编码算法减少了压缩的时间,提高了图像压缩的效率,增强了重构图像的效果,可以运用到实际应用中。
With the rapid development of maritime traffic, ocean traffic accidents are increasing. The voyage data recorder can records navigation data including image and audio data, which can provide evidence for troubleshooting and accident investigation. In the storage space of navigation data, ship-borne radar images accounted for a large part, therefore, in the process of transmission and storage, how to compress the radar image based on reducing the storage volume and achieving a good compression is an urgent matter to be solved. At present, as most of the voyage recorder radar products adopted the MPEG standard in radar image compression, however, this method doesn't take into account the characteristics of radar image, therefore, it's necessary to carry out new research on the ship borne radar image compression technology.
In this paper, as the successful application in image compression with wavelet transform, a combined method based on scheme lifting algorithm, SPIHT and arithmetic coding is put forward for radar image compression. In the application of wavelet transform to compress the radar image, the wavelet function and the layer of decomposition must be chosen. According to lots of research materials, the dissertation summarizes the effect of the digital characteristics of wavelet function to image compression performance. And based on it, selects several representative wavelet functions, nature and radar image, and compares the compression ratio and images' PSNR through experiment, at last, selects the ideal wavelet function and layer of decomposition, provides a reference for the practical application.
In this dissertation, the classical radar image compression methods based on the wavelet transform, EZW and SPIHT methods are compared, by comparing the compression speed and reconstruction effect between the two methods, the time consumption is reduced and compression effect is better in SPIHT method which can be applied in practical application.
本文根据雷达图像的特征以及小波变换在图像压缩方面的成功应用,提出了利用提升小波变换和SPIHT算法与算术编码相结合的方法对雷达图像进行压缩,并将此方法与其他算法的压缩速度和压缩图像效果进行比较。选取不同小波基和分解层数会对图像的压缩性能造成影响,所以小波变换在雷达图像压缩的应用中,小波函数以及分解层数的选择是必须解决的问题。本文根据大量的文献资料,归纳出小波函数的数字特性对图像压缩性能的影响,并以此为依据,选取几种具有代表性的小波函数以及自然图像和雷达图像,通过实验,比较其压缩比和图像的峰值信噪比,最后,选择出较为理想的小波函数和分解层数,为实际应用提供了参考。
文章还对比分析了基于小波变换的图像压缩的经典算法：EZW和SPIHT算法,对两算法的压缩速度与重构图像效果进行比较,从实验结果可以看出SPIHT编码算法减少了压缩的时间,提高了图像压缩的效率,增强了重构图像的效果,可以运用到实际应用中。
With the rapid development of maritime traffic, ocean traffic accidents are increasing. The voyage data recorder can records navigation data including image and audio data, which can provide evidence for troubleshooting and accident investigation. In the storage space of navigation data, ship-borne radar images accounted for a large part, therefore, in the process of transmission and storage, how to compress the radar image based on reducing the storage volume and achieving a good compression is an urgent matter to be solved. At present, as most of the voyage recorder radar products adopted the MPEG standard in radar image compression, however, this method doesn't take into account the characteristics of radar image, therefore, it's necessary to carry out new research on the ship borne radar image compression technology.
In this paper, as the successful application in image compression with wavelet transform, a combined method based on scheme lifting algorithm, SPIHT and arithmetic coding is put forward for radar image compression. In the application of wavelet transform to compress the radar image, the wavelet function and the layer of decomposition must be chosen. According to lots of research materials, the dissertation summarizes the effect of the digital characteristics of wavelet function to image compression performance. And based on it, selects several representative wavelet functions, nature and radar image, and compares the compression ratio and images' PSNR through experiment, at last, selects the ideal wavelet function and layer of decomposition, provides a reference for the practical application.
In this dissertation, the classical radar image compression methods based on the wavelet transform, EZW and SPIHT methods are compared, by comparing the compression speed and reconstruction effect between the two methods, the time consumption is reduced and compression effect is better in SPIHT method which can be applied in practical application.
引文
[1]中华人民共和国交通部海事局.船舶航行数据记录仪技术条件和检验程序[Z].2001.
[2]Jonggu Kang, Bokjin Youm, Deokhwan Cho et al. Development of Remote Alarm Module with Playback functions in Voyage Data Recorder[C].2009 ICCAS-SICE,2009:5181-5184.
[3]刘敬贤.VDR与海事调查[J].中国水运.2003,(2)：12-13.
[4]金建海,刘爱华.船用黑匣子中主机与外部传感器数据通信的实现[J].船舶力学,2002,(8)：108-113.
[5]The new Simplified Voyage Data Recorder SVDR-C[J]. Schiff und Hafen,2007,59(6):144-145.
[6]沙瀛.雷达图像的分形压缩编码[D].大连海事大学,1998.
[7]陈鹏,郭伟.小波多分辨率分解的雷达视频压缩研究[J].计算机工程与应用,2005,41(21)：83-85.
[8]Parkes S M, Clifton H L. Compression of raw SAR and SAR image data[J]. International Journal of Remote Sensing, Vol.20, No.18,1999.
[9]YING Shi-jun. Radar Image Compression Using Wavelet Based on SPIHT Algorithm[J].中国航海,2007,(1)35-42.
[10]董鹏曙等.高分辨率雷达图像压缩编码算法及实现[J].系统工程与电子技术,2009,1(31)54-56.
[11]X wu Lossless Compression of Continuous Tone Images via Context Selection, Quantization and Model ing[J]. IEEE Trans. On Image Processing,1997,6(5):656-664.
[12]杨长生.图像与声音压缩技术[M].杭州.浙江大学出版社,2000.
[13]张霞等.矢量量化在图像压缩编码中的应用进展[J].数据采集与处理,1999,2(1)：52-56.
[14]肖田元等.分形及分形图像压缩技术[J].中国图像图形学报,1998,23(11)：970-976.
[15]朱庆生等.一种基于小波变换的静态图像压缩编码方法[J].计算机工程与科学,1997,5(3)：9-12.
[16]张福安,郭伟.一种雷达图像信号的压缩方法[J].电子对抗技术,2004,5(34)：31-34.
[17]黑延彬,熊璋.基于信号特征的雷达图像无损压缩算法[J].计算机工程与设计,2005,26(1)：272-273.
[18]李天伟,贾传荧,郭模灿.VDR雷达图像的ROI图像编码压缩算法[J].中国造船,2007,15(12)：96-99.
[19]王仁龙,郝燕玲,刘营.基于块为长的小波嵌入式编码算法[J].光学精密工程,2008,7 (16)1317-1321.
[20]潘葳等.基于EZW与SPIHT的雷达图像压缩研究[J].科学技术与工程,2010,11(32)8051-8053.
[21]Sten Warnfeldt. How can the VDR prevent accidents and improve the Safety of a vessel[J]. International Symposium on Transportation Recorders.1999,5(2)3-5.
[22]姜海秀.雷达图像压缩的研究[D].大连海事大学,2007.
[23]陈宇里.VDR雷达图像压缩技术及测试系统研究[D].上海海事大学,2004.
[24]Chen Yongchun, Han Yueqiu, He Pei-kun. A New Algorithm for Lossless Radar Data Compression [J]. Journal of Beijing University of Technology.1997,17(6):697-700.
[25]Mallat S. Multi frequency channel decomposition of image and wavelet model[J]. IEEE Trans, On ASSP.1989,37(12):2091-2110.
[26]Mallat S. Multiresolution approximation and wavelet orthonormal bases of L2. Trans. Of the American Math. Society.1989,135(1):69-87.
[27]Daubechies I. Orthonormal bases of compactly supported wavelets[J]. Communications on Pure and Application Mathematics.1988,41 (8):906-996.
[28]Daubechies I. Ten Lectures on Wavelets[M]. SIAM,1992.
[29]伯勒斯,戈皮纳持.程正兴译.小波与小波变换导论[M].北京：机械工业出版社,2008.
[30]米克斯,奥莱伊尼恰克(美).杨志华,杨力华译.小波基础及应用教程[M].北京：机械工业出版社,2006.
[31]Burrus, C. S. GoPinath, Ramesh A. Introduction to wavelets and wavelets transforms: a primer[M]. Beijing:China machine Press,2005.
[32]Boggess, Albert. Narcowich, Francis J. A first course in wavelets with Fourier analysis[M]. Beijing:Publishing House of Electronics Industry,2002.
[33]程正兴,杨守志,冯晓霞.小波分析的理论、算法、进展和应用[M].北京：国防工业出版社,2007.
[34]P. Wojtaszczyk. A Mathematical Introduction to Wavelets. Number 37 in London Mathematical Society Student Texts[M]. Cambridge University Press, New York,1997.
[35]M Anonini, M Barland, P Mathieu, I Daubechies. Image coding using wavelet transform [J]. IEEE Trans. Image Processing.1992,2(1):205-220.
[36]Ai-Li Wang, Ye Zhang, Yan-Feng Gu et al. Simultaneous Speckle Reduction and SAR Image Compression Using Multiwavelet Transform [J]. Journal of Electronic Science and Technology of China,2007,5(2):163-166.
[37]何小海,杨晓梅.数字图像通信[M].成都：四川大学出版社,2010.
[38]陈升来,黄廉卿,郭静寰.基于整型提升小波变换的图像处理及DSP实现[J].光学精密工程,2006,14(3)：498-502.
[39]孔凡邨,陈宇里.船用导航雷达图像压缩小波函数选择的比较研究[J].航海技术,2004,(4)：39-41.
[40]Grgic S, Grgic M, Zovko-Cihlar B. Performance Analysis of Image Compression Using Wavelets[J]. IEEE Trans on Industrial Electronics,2005,48(3):682-695.
[41]Cohen A, Daubechies I, Feauvean J C. Biorthogonal bases of compactly supported wavelets [J]. Communications on Pure and Application Mathematics,1992,45(3):485-560.
[42]Michael D, Faouzi Kossentini. Reversible integer-to-integer wavelet transforms for image compression:performance evaluation and analysis[J]. IEEE Trans on Image Processing,2009, (6):1010-1024.
[43]PATEL V M. EASLEY G R, HEALY D M, et al. Compressed synthetic aperture radar[C]. IEEE Journal of Selected Topics in Signal Processing,2010,4(2):244-254.
[44]Shapiro J. Embedded image coding using zerotrees of wavelets coeff icients[J]. IEEE Transactions on Signal Processing,1993,41(12):3445-3462.
[45]Tohum oglu G, Sezgin K E·ECG signal compression by multi-iteration EZW coding for different wavelets and thresholds[J]. Computers in Biology and Medicine,2007, 37(2):173—182.
[46]朱希安,宁书年,金声震等.嵌入式小波零树压缩算法的基本原理[J].中国煤田地质,2003,15(4)：43-48.
[47]靳济芳Visual C++小波变换技术与工程实践[M].北京：人民邮电出版社,2004.
[48]姚敏,赵敏.改进的高效EZW遥感图像压缩方法研究[J].电子科技大学学报,2009,38(4)：525-528.
[49]Hong Pan, Su, W. C; Law, N. F; Efficient and low—complexity image coding with the lifting scheme and modified SPIHT[C]. IEEE International Joint Conference on Neural Networks,2008,12 (5):1959-1963.
[50]Jyothesw ar J, M ahapatra S. Efficient FPGA implementation of DWT and modified SPIHT for lossless image compression. Journal of Systems Architecture,2007,5 (8):369-378.
[51]郭维树.小波变换在图像压缩中的改进算法[J].电脑知识与技术,2008,3(24)1253-1254.
[2]Jonggu Kang, Bokjin Youm, Deokhwan Cho et al. Development of Remote Alarm Module with Playback functions in Voyage Data Recorder[C].2009 ICCAS-SICE,2009:5181-5184.
[3]刘敬贤.VDR与海事调查[J].中国水运.2003,(2)：12-13.
[4]金建海,刘爱华.船用黑匣子中主机与外部传感器数据通信的实现[J].船舶力学,2002,(8)：108-113.
[5]The new Simplified Voyage Data Recorder SVDR-C[J]. Schiff und Hafen,2007,59(6):144-145.
[6]沙瀛.雷达图像的分形压缩编码[D].大连海事大学,1998.
[7]陈鹏,郭伟.小波多分辨率分解的雷达视频压缩研究[J].计算机工程与应用,2005,41(21)：83-85.
[8]Parkes S M, Clifton H L. Compression of raw SAR and SAR image data[J]. International Journal of Remote Sensing, Vol.20, No.18,1999.
[9]YING Shi-jun. Radar Image Compression Using Wavelet Based on SPIHT Algorithm[J].中国航海,2007,(1)35-42.
[10]董鹏曙等.高分辨率雷达图像压缩编码算法及实现[J].系统工程与电子技术,2009,1(31)54-56.
[11]X wu Lossless Compression of Continuous Tone Images via Context Selection, Quantization and Model ing[J]. IEEE Trans. On Image Processing,1997,6(5):656-664.
[12]杨长生.图像与声音压缩技术[M].杭州.浙江大学出版社,2000.
[13]张霞等.矢量量化在图像压缩编码中的应用进展[J].数据采集与处理,1999,2(1)：52-56.
[14]肖田元等.分形及分形图像压缩技术[J].中国图像图形学报,1998,23(11)：970-976.
[15]朱庆生等.一种基于小波变换的静态图像压缩编码方法[J].计算机工程与科学,1997,5(3)：9-12.
[16]张福安,郭伟.一种雷达图像信号的压缩方法[J].电子对抗技术,2004,5(34)：31-34.
[17]黑延彬,熊璋.基于信号特征的雷达图像无损压缩算法[J].计算机工程与设计,2005,26(1)：272-273.
[18]李天伟,贾传荧,郭模灿.VDR雷达图像的ROI图像编码压缩算法[J].中国造船,2007,15(12)：96-99.
[19]王仁龙,郝燕玲,刘营.基于块为长的小波嵌入式编码算法[J].光学精密工程,2008,7 (16)1317-1321.
[20]潘葳等.基于EZW与SPIHT的雷达图像压缩研究[J].科学技术与工程,2010,11(32)8051-8053.
[21]Sten Warnfeldt. How can the VDR prevent accidents and improve the Safety of a vessel[J]. International Symposium on Transportation Recorders.1999,5(2)3-5.
[22]姜海秀.雷达图像压缩的研究[D].大连海事大学,2007.
[23]陈宇里.VDR雷达图像压缩技术及测试系统研究[D].上海海事大学,2004.
[24]Chen Yongchun, Han Yueqiu, He Pei-kun. A New Algorithm for Lossless Radar Data Compression [J]. Journal of Beijing University of Technology.1997,17(6):697-700.
[25]Mallat S. Multi frequency channel decomposition of image and wavelet model[J]. IEEE Trans, On ASSP.1989,37(12):2091-2110.
[26]Mallat S. Multiresolution approximation and wavelet orthonormal bases of L2. Trans. Of the American Math. Society.1989,135(1):69-87.
[27]Daubechies I. Orthonormal bases of compactly supported wavelets[J]. Communications on Pure and Application Mathematics.1988,41 (8):906-996.
[28]Daubechies I. Ten Lectures on Wavelets[M]. SIAM,1992.
[29]伯勒斯,戈皮纳持.程正兴译.小波与小波变换导论[M].北京：机械工业出版社,2008.
[30]米克斯,奥莱伊尼恰克(美).杨志华,杨力华译.小波基础及应用教程[M].北京：机械工业出版社,2006.
[31]Burrus, C. S. GoPinath, Ramesh A. Introduction to wavelets and wavelets transforms: a primer[M]. Beijing:China machine Press,2005.
[32]Boggess, Albert. Narcowich, Francis J. A first course in wavelets with Fourier analysis[M]. Beijing:Publishing House of Electronics Industry,2002.
[33]程正兴,杨守志,冯晓霞.小波分析的理论、算法、进展和应用[M].北京：国防工业出版社,2007.
[34]P. Wojtaszczyk. A Mathematical Introduction to Wavelets. Number 37 in London Mathematical Society Student Texts[M]. Cambridge University Press, New York,1997.
[35]M Anonini, M Barland, P Mathieu, I Daubechies. Image coding using wavelet transform [J]. IEEE Trans. Image Processing.1992,2(1):205-220.
[36]Ai-Li Wang, Ye Zhang, Yan-Feng Gu et al. Simultaneous Speckle Reduction and SAR Image Compression Using Multiwavelet Transform [J]. Journal of Electronic Science and Technology of China,2007,5(2):163-166.
[37]何小海,杨晓梅.数字图像通信[M].成都：四川大学出版社,2010.
[38]陈升来,黄廉卿,郭静寰.基于整型提升小波变换的图像处理及DSP实现[J].光学精密工程,2006,14(3)：498-502.
[39]孔凡邨,陈宇里.船用导航雷达图像压缩小波函数选择的比较研究[J].航海技术,2004,(4)：39-41.
[40]Grgic S, Grgic M, Zovko-Cihlar B. Performance Analysis of Image Compression Using Wavelets[J]. IEEE Trans on Industrial Electronics,2005,48(3):682-695.
[41]Cohen A, Daubechies I, Feauvean J C. Biorthogonal bases of compactly supported wavelets [J]. Communications on Pure and Application Mathematics,1992,45(3):485-560.
[42]Michael D, Faouzi Kossentini. Reversible integer-to-integer wavelet transforms for image compression:performance evaluation and analysis[J]. IEEE Trans on Image Processing,2009, (6):1010-1024.
[43]PATEL V M. EASLEY G R, HEALY D M, et al. Compressed synthetic aperture radar[C]. IEEE Journal of Selected Topics in Signal Processing,2010,4(2):244-254.
[44]Shapiro J. Embedded image coding using zerotrees of wavelets coeff icients[J]. IEEE Transactions on Signal Processing,1993,41(12):3445-3462.
[45]Tohum oglu G, Sezgin K E·ECG signal compression by multi-iteration EZW coding for different wavelets and thresholds[J]. Computers in Biology and Medicine,2007, 37(2):173—182.
[46]朱希安,宁书年,金声震等.嵌入式小波零树压缩算法的基本原理[J].中国煤田地质,2003,15(4)：43-48.
[47]靳济芳Visual C++小波变换技术与工程实践[M].北京：人民邮电出版社,2004.
[48]姚敏,赵敏.改进的高效EZW遥感图像压缩方法研究[J].电子科技大学学报,2009,38(4)：525-528.
[49]Hong Pan, Su, W. C; Law, N. F; Efficient and low—complexity image coding with the lifting scheme and modified SPIHT[C]. IEEE International Joint Conference on Neural Networks,2008,12 (5):1959-1963.
[50]Jyothesw ar J, M ahapatra S. Efficient FPGA implementation of DWT and modified SPIHT for lossless image compression. Journal of Systems Architecture,2007,5 (8):369-378.
[51]郭维树.小波变换在图像压缩中的改进算法[J].电脑知识与技术,2008,3(24)1253-1254.