一种易于硬件实现的图像有损压缩算法
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摘要
随着现代空间技术的高速发展,遥感图像在环境监测、卫星云图、军事侦察、地质勘探等方面得到了广泛应用。而高分辨率通信卫星的使用使得从空间传输到地面站的数据量越来越大,为了减少和缓冲存储空间、降低传输带宽、在给定的压缩码率的条件下,尽可能的减少数据的传输时间,就需要对原始数据进行高效的压缩。
空间数据系统咨询委员会(Consultative Committee for Space Data Systems简称CCSDS)于2005年11月正式提出了针对空间遥感图像数据压缩标准,此算法的核心为小波变换和比特平面编码算法,其结构简单、复杂度低、易于硬件实现、并能实现对空间数据的实时处理,从而可以广泛应用于空间探测。本文的主要工作如下：
(1)了解小波基本理论并深入研究CCSDS图像数据压缩标准中小波变换方法。因主要是对图像有损压缩算法的研究,故选择标准中的9／7离散小波变换。
(2)对CCSDS图像数据压缩标准提出的算法作了深入研究,通过段头编码、直流系数量化编码、块交流比特深度编码和比特平面编码方法有效实现图像有损压缩,经过系统仿真对其压缩性能进行分析,证明此算法有利于提高重建图像的质量。
(3)根据CCSDS图像压缩算法标准中对直流系数量化编码和交流系数比特深度编码中的参数K和熵编码中长度分别为3bit码字(choicel)和4bit码字(choice2)的编码方式的选择实现数据的渐进性编码,产生的码流具有内嵌特性,即可以对任意码流进行截取和译码,实现对码率的有效控制。
(4)通过限率失真优化方法进一步优化CCSDS图像压缩算法
With the rapid development of modern space technology, Remote-sensing images have been widely used in environmental monitoring、satellite images、military reconnaissance、geological exploration etc. The use of high resolution communications satellites makes the amount of data transported from the space station to the ground station is growing. In order to reduce and buffer storage space、reduce the transmission bandwidth、as far as possible to reduce data transmission time in a given condition, we need to carry out the high-effect compression on the original data.
Consultative Committee for Space Data Systems(CCSDS for short) has proposed the image data compression standard for space remote sensing image formally in November 2005.The core of this algorithm is wavelet transform and bit plane encoding, owing to its simple structure、low complexity、easy hardware implementation and can achieve real-time processing of spatial data, it can be widely used in space exploration. The main work of this paper is as follows:
(1) Learn the basic theory of wavelet transform and make a deep study of wavelet transform in CCSDS image data compression standard. Mainly for image lossy compression algorithm, so I have chosen the 9/7 discrete wavelet transform of the standard.
(2) Make a deep study of the algorithm which is proposed in CCSDS image data compression standard.Though segment header encoding、DC coefficient quantization encoding、AC bit depth encoding in block、bit plane encoding, it has make a effectively compression on image. After system simulation to analyze the performance of its compression, it's proved that this algorithm is helpful in improving the quality of reconstructed image.
(3) Through selecting the parameters K of DC coefficients quantization coding and AC bit depth encoding and choosing the code method of 3-bit words (choice 1) or 4-bit words (choice2) in entropy coding implement the data progressiveness coding. These code streams have embedded feature, then any code streams can be truncated and decoded, and control the code rate efficiently.
(4) Limit of rate distortion optimization has made a further optimization of CCSDS image compression algorithm.
空间数据系统咨询委员会(Consultative Committee for Space Data Systems简称CCSDS)于2005年11月正式提出了针对空间遥感图像数据压缩标准,此算法的核心为小波变换和比特平面编码算法,其结构简单、复杂度低、易于硬件实现、并能实现对空间数据的实时处理,从而可以广泛应用于空间探测。本文的主要工作如下：
(1)了解小波基本理论并深入研究CCSDS图像数据压缩标准中小波变换方法。因主要是对图像有损压缩算法的研究,故选择标准中的9／7离散小波变换。
(2)对CCSDS图像数据压缩标准提出的算法作了深入研究,通过段头编码、直流系数量化编码、块交流比特深度编码和比特平面编码方法有效实现图像有损压缩,经过系统仿真对其压缩性能进行分析,证明此算法有利于提高重建图像的质量。
(3)根据CCSDS图像压缩算法标准中对直流系数量化编码和交流系数比特深度编码中的参数K和熵编码中长度分别为3bit码字(choicel)和4bit码字(choice2)的编码方式的选择实现数据的渐进性编码,产生的码流具有内嵌特性,即可以对任意码流进行截取和译码,实现对码率的有效控制。
(4)通过限率失真优化方法进一步优化CCSDS图像压缩算法
With the rapid development of modern space technology, Remote-sensing images have been widely used in environmental monitoring、satellite images、military reconnaissance、geological exploration etc. The use of high resolution communications satellites makes the amount of data transported from the space station to the ground station is growing. In order to reduce and buffer storage space、reduce the transmission bandwidth、as far as possible to reduce data transmission time in a given condition, we need to carry out the high-effect compression on the original data.
Consultative Committee for Space Data Systems(CCSDS for short) has proposed the image data compression standard for space remote sensing image formally in November 2005.The core of this algorithm is wavelet transform and bit plane encoding, owing to its simple structure、low complexity、easy hardware implementation and can achieve real-time processing of spatial data, it can be widely used in space exploration. The main work of this paper is as follows:
(1) Learn the basic theory of wavelet transform and make a deep study of wavelet transform in CCSDS image data compression standard. Mainly for image lossy compression algorithm, so I have chosen the 9/7 discrete wavelet transform of the standard.
(2) Make a deep study of the algorithm which is proposed in CCSDS image data compression standard.Though segment header encoding、DC coefficient quantization encoding、AC bit depth encoding in block、bit plane encoding, it has make a effectively compression on image. After system simulation to analyze the performance of its compression, it's proved that this algorithm is helpful in improving the quality of reconstructed image.
(3) Through selecting the parameters K of DC coefficients quantization coding and AC bit depth encoding and choosing the code method of 3-bit words (choice 1) or 4-bit words (choice2) in entropy coding implement the data progressiveness coding. These code streams have embedded feature, then any code streams can be truncated and decoded, and control the code rate efficiently.
(4) Limit of rate distortion optimization has made a further optimization of CCSDS image compression algorithm.
引文
[1]冈萨雷斯编著.数字图像处理(第二版)[M].北京：电子工业出版社,2007
[2]张雪松,倪国强,周立伟等.图像编码技术发展综述[J].光学技术,1997,5(3)：37-40
[3]徐梦侠.图像编码的进展[J].通信学报,1993,3(14)：40-41
[4]邓家先.遥感图像编码技术研究[D].西安：西安电子科技大学,2004
[5]陈静.图像压缩编码技术的发展历程及前景[J].安徽电子信息职业学院学报,2009,5(8)：39-40
[6]邓家先,康耀红编著.信息论与编码[M].西安：西安电子科技大学出版社,2007
[7]陈欣琳,魏东,金亮.视频图像的压缩传输技术研究[J].硅谷,2009,8(15)：29-30
[8]张照炎.空间数据系统咨询委员会简介[J].国际太空,2009,3：26-27
[9]魏凌.CCSDS_AOS建议的研究[J].研究与应用,2004,5(30)：34-35
[10]宋鹏,张晓琳.关于CCSDS无损数据压缩建议的初步研究[J].遥测遥控,2000,1(22)：8-13
[11]C.Sidney Burrus,Ramesh A.Gopinath等著.Introduction to Wavelets and Wavelet Transforms[M].北京：机械工业出版社.2007
[12]陈妍.基于小波变换的图像数据压缩算法[J].天津市财贸管理干部学院学报,2008,4(10)：36-38
[13]王培茂.离散余弦变换与小波变换的比较[J].河北理工学院学报,2005,3(27)：53-54
[14]陈耀明.小波变换在图像数据压缩中的应用[J].现在电子技术,2007,6：136-137
[15]Image Data Compression Recommendation for Space Data System Standards CCSDS 122.0-B-1[S]
[16]杨波,汪同庆,叶俊勇.一种二值图像的有损压缩方法[J].计算机应用2002,22(3)：37-38
[17]罗扬,谭汉松.图像的小波压缩技术及研究进展[J].长沙大学学报.2004,4(18)：47-48
[18]田宝凤,徐抒岩,孙荣春,王昕,闫得杰.一种适合星上应用的遥感图像有损压缩算法[J].光学精密工程,2006,14(4)：725-726
[19]王继东,鲁琴,罗武胜,肖学敏.位平面算术编码的编码分离与MQ编码器改进[J].中国图象图形学报,2007,10(12)：1806-1807
[20]李国军,马凤铭.提升小波变换及其FPGA实现[J].鞍山师范学院学报,2004,6(4)：25-27
[21]高广春.第二代小波变换理论及其在信号和图像编码算法中的应用[D].2004
[22]薛坚.提升小波变换的应用与硬件实现[D].2008
[23]邓家先,吴成柯,陈军,李云松.二次率失真优化截取的感兴趣区域编码[J].系统工程与电子技术.2003,12(25)：1532-1535
[24]杨永明,许超.一个基于小波包分解的率失真最优化块分割图像编码算法[J].信息科学.2008,8(38)：1204-1219
[25]Shapiro J M. Embedded image coding using zerotrees of wavelet coefficients.IEEE Trans Signal Process[J].1993,41(10):3445-3462
[26]Said A,Pearlman W A.A new.fast and efficient image codec based on set partitioning in hierarchical trees[J].IEEE Trans Circ Syst Video Technol.1996,6(6):243-250
[27]Liu Z,Karam L J.An efficient embedded zerotree wavelet image codec based on intraband partitioning.IEEE Int Conf Image Process [J].2000,3:162-165
[2]张雪松,倪国强,周立伟等.图像编码技术发展综述[J].光学技术,1997,5(3)：37-40
[3]徐梦侠.图像编码的进展[J].通信学报,1993,3(14)：40-41
[4]邓家先.遥感图像编码技术研究[D].西安：西安电子科技大学,2004
[5]陈静.图像压缩编码技术的发展历程及前景[J].安徽电子信息职业学院学报,2009,5(8)：39-40
[6]邓家先,康耀红编著.信息论与编码[M].西安：西安电子科技大学出版社,2007
[7]陈欣琳,魏东,金亮.视频图像的压缩传输技术研究[J].硅谷,2009,8(15)：29-30
[8]张照炎.空间数据系统咨询委员会简介[J].国际太空,2009,3：26-27
[9]魏凌.CCSDS_AOS建议的研究[J].研究与应用,2004,5(30)：34-35
[10]宋鹏,张晓琳.关于CCSDS无损数据压缩建议的初步研究[J].遥测遥控,2000,1(22)：8-13
[11]C.Sidney Burrus,Ramesh A.Gopinath等著.Introduction to Wavelets and Wavelet Transforms[M].北京：机械工业出版社.2007
[12]陈妍.基于小波变换的图像数据压缩算法[J].天津市财贸管理干部学院学报,2008,4(10)：36-38
[13]王培茂.离散余弦变换与小波变换的比较[J].河北理工学院学报,2005,3(27)：53-54
[14]陈耀明.小波变换在图像数据压缩中的应用[J].现在电子技术,2007,6：136-137
[15]Image Data Compression Recommendation for Space Data System Standards CCSDS 122.0-B-1[S]
[16]杨波,汪同庆,叶俊勇.一种二值图像的有损压缩方法[J].计算机应用2002,22(3)：37-38
[17]罗扬,谭汉松.图像的小波压缩技术及研究进展[J].长沙大学学报.2004,4(18)：47-48
[18]田宝凤,徐抒岩,孙荣春,王昕,闫得杰.一种适合星上应用的遥感图像有损压缩算法[J].光学精密工程,2006,14(4)：725-726
[19]王继东,鲁琴,罗武胜,肖学敏.位平面算术编码的编码分离与MQ编码器改进[J].中国图象图形学报,2007,10(12)：1806-1807
[20]李国军,马凤铭.提升小波变换及其FPGA实现[J].鞍山师范学院学报,2004,6(4)：25-27
[21]高广春.第二代小波变换理论及其在信号和图像编码算法中的应用[D].2004
[22]薛坚.提升小波变换的应用与硬件实现[D].2008
[23]邓家先,吴成柯,陈军,李云松.二次率失真优化截取的感兴趣区域编码[J].系统工程与电子技术.2003,12(25)：1532-1535
[24]杨永明,许超.一个基于小波包分解的率失真最优化块分割图像编码算法[J].信息科学.2008,8(38)：1204-1219
[25]Shapiro J M. Embedded image coding using zerotrees of wavelet coefficients.IEEE Trans Signal Process[J].1993,41(10):3445-3462
[26]Said A,Pearlman W A.A new.fast and efficient image codec based on set partitioning in hierarchical trees[J].IEEE Trans Circ Syst Video Technol.1996,6(6):243-250
[27]Liu Z,Karam L J.An efficient embedded zerotree wavelet image codec based on intraband partitioning.IEEE Int Conf Image Process [J].2000,3:162-165