3D-DCT自适应彩色图像压缩算法的研究
摘要
由于数字图像信息给人以直观具体的立体彩色形象,并且具有传输质量好、可靠性高、易于加密等优点,因而广泛应用于人们的日常生活中。但随着人们对清晰度要求的不断提高,数字图像的信息量不断增大,消耗了大量的存储空间和传输带宽。因此,在保持一定编码质量的前提下,如何减少信息量以达到数据压缩是一个值得研究的课题。
离散余弦变换(DCT)是一种较好的基于频率域的压缩算法,该算法主要依据的原理是：在一幅图像中,其直流和低频分量占主要部分,故可通过舍去部分次要的高频分量来达到压缩的目的。又因该算法具有极为接近K-L变换的去相关性并且有快速算法,所以被各图像及视频压缩的国际标准广泛采用。
随着计算机处理能力的提高,使早期提出的三维离散余弦变换(3D-DCT)的应用成为可能。3D-DCT技术就是通过进一步压缩彩色图像中因各颜色分量所具有相同纹理,边缘和灰度变化梯度所产生的冗余,从而达到提高图像压缩的目的。
本文提出了一种以峰值信噪比(PSNR)和压缩比(CR)为参考标准的基于3D-DCT的自适应图像压缩算法。该算法主要提出了一种与二值编码器(TRE)相结合的新的量化方法,并将其应用在对重构图像质量影响最大的几个三维离散余弦变换后的系数上,以达到提高CR的目的。本文最后使用MATLAB软件对所提出的算法进行了仿真并与当前流行的JPEG编码进行比较,证明文中算法在追求较高CR的情况下也保证了较好的PSNR。
As the digital image information provides visualize specific three-dimensional color image and has some advantages such as good transmission quality, high reliability and easy encryption, it is widely used in people's daily life. However, with the rising requirements of digital image definition, the quantity of digital image information is increasing ceaselessly, which consumes a large amount of storage space and transmission bandwidth. Therefore, how to reduce the amount of information to achieve data compression while maintaining a certain encoding quality becomes a topic worthy of study.
Discrete cosine transform (DCT) is a better compression algorithm based on frequency domain, since it can eliminate by the high frequency component part of secondary image to achieve the aim of compression while fully preserving the DC and low frequency components which are the main part of the image. The decorrelation of the transform is close to the optimal K-L transform and there is a fast algorithm for DCT, so DCT is widely adopted by many international image and video compression standards.
With the enhancement of computer processing ability, the application of three-dimensional discrete cosine transform(3D-DCT) which was put forward early becomes possible.3D-DCT technology can eliminate by the redundancy of the similar texture, edge and gray level gradient to reach the high compression ratio.
In this paper, an adaptive color image compression algorithm based on three-dimensional discrete cosine transform is proposed. The algorithm use PSNR and CR as its reference standard. For the aim to obtain the best possible compression ratio CR, a new quantitative method combined with two role encoder(TRE) is proposed and applies to some coefficients of three-dimensional discrete cosine transform which have more impact on reconstructed image quality. Finally this paper uses MATLAB for the simulation. With the popular JPEG coding for comparison, we find that the algorithm makes a high compression ratio and also ensures a better PSNR.
离散余弦变换(DCT)是一种较好的基于频率域的压缩算法,该算法主要依据的原理是：在一幅图像中,其直流和低频分量占主要部分,故可通过舍去部分次要的高频分量来达到压缩的目的。又因该算法具有极为接近K-L变换的去相关性并且有快速算法,所以被各图像及视频压缩的国际标准广泛采用。
随着计算机处理能力的提高,使早期提出的三维离散余弦变换(3D-DCT)的应用成为可能。3D-DCT技术就是通过进一步压缩彩色图像中因各颜色分量所具有相同纹理,边缘和灰度变化梯度所产生的冗余,从而达到提高图像压缩的目的。
本文提出了一种以峰值信噪比(PSNR)和压缩比(CR)为参考标准的基于3D-DCT的自适应图像压缩算法。该算法主要提出了一种与二值编码器(TRE)相结合的新的量化方法,并将其应用在对重构图像质量影响最大的几个三维离散余弦变换后的系数上,以达到提高CR的目的。本文最后使用MATLAB软件对所提出的算法进行了仿真并与当前流行的JPEG编码进行比较,证明文中算法在追求较高CR的情况下也保证了较好的PSNR。
As the digital image information provides visualize specific three-dimensional color image and has some advantages such as good transmission quality, high reliability and easy encryption, it is widely used in people's daily life. However, with the rising requirements of digital image definition, the quantity of digital image information is increasing ceaselessly, which consumes a large amount of storage space and transmission bandwidth. Therefore, how to reduce the amount of information to achieve data compression while maintaining a certain encoding quality becomes a topic worthy of study.
Discrete cosine transform (DCT) is a better compression algorithm based on frequency domain, since it can eliminate by the high frequency component part of secondary image to achieve the aim of compression while fully preserving the DC and low frequency components which are the main part of the image. The decorrelation of the transform is close to the optimal K-L transform and there is a fast algorithm for DCT, so DCT is widely adopted by many international image and video compression standards.
With the enhancement of computer processing ability, the application of three-dimensional discrete cosine transform(3D-DCT) which was put forward early becomes possible.3D-DCT technology can eliminate by the redundancy of the similar texture, edge and gray level gradient to reach the high compression ratio.
In this paper, an adaptive color image compression algorithm based on three-dimensional discrete cosine transform is proposed. The algorithm use PSNR and CR as its reference standard. For the aim to obtain the best possible compression ratio CR, a new quantitative method combined with two role encoder(TRE) is proposed and applies to some coefficients of three-dimensional discrete cosine transform which have more impact on reconstructed image quality. Finally this paper uses MATLAB for the simulation. With the popular JPEG coding for comparison, we find that the algorithm makes a high compression ratio and also ensures a better PSNR.
引文
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[3]李琳.基于小波变换的JPEG图像压缩算法研究[D].西安：西安科技大学,2010.
[4]杜广环.基于小波变换图像压缩编码研究的现状与发展[J].科技创新导报.2011,(10)：83-84.
[5]桑爱军,陈贺新.三维矩阵彩色图像WDCT压缩编码[J].电子学报.2002,30(4)：594-597.
[6]翁银.基于JPEG2000的医学图像压缩的研究与应用[D].西安：西安电子科技大学,2008.
[7]茅文深,陈雪峰,常传文.阈值对游程编码压缩率影响分析[J].计算机与数字工程.2008,36(9)：31-33.
[8]孔凡龙,程思远,关迅.浅谈无损压缩算法[J].电脑知识与技术.2011,7(22)：5466-5467.
[9]彭芬H.264/AVC中的CABAC编码技术[J].山西电子技术.2007,(3)：86-87.
[10]郑翠芳.几种常用无损数据压缩算法研究[J].计算机技术与发展.2011,21(9)：73-76.
[11]徐立中,王会斌.视频图像压缩编码方法及国际标准[J].水利水文自动化.1998,(3)：1-5.
[12]于松亭.变换域编码在JPEG图像压缩中的应用[J].数字技术与应用.2011,(11)：122-123.
[13]Abadpour A, Kasaei S. Color PCA eigenimages and their application to compression and watermarking[J]. Image and Vision Computing.2008,26:878-890.
[14]Makrogiannis S, Economou G, Fotopoulos S. Region oriented compression of color images using fuzzy inference and fast merging[J]. Pattern Recognition.2002,35:1807-1820.
[15]Alkholidi A, Alfalou A, Hamam H. A new approach for optical colored image compression using the jpeg standards[J]. Signal Processing.2007,87:569-583.
[16]Chikouche D, Benzid R, Bentoumi M. Application of the dct and arithmetic coding to medical image compression[C]. IEEE third international conference on information and communication technologies: from theory to applica-tions,2008. ICTTA 2008.2008:1-5.
[17]朱竹清.多标准离散余弦变换算法及VLSI体系研究与实现[D].杭州：杭州电子科技大学,2009.
[18]张春田.视频信号压缩编码第三讲预测编码[J].广播与电视技术.1995,22(1)：54-59.
[19]http://www.bokee.net/newcirclemodule/article_viewEntry.do?id=1412197&circleId=132445
[20]陶长武,蔡自兴.现代图像压缩编码技术[J].信息技术.2007,(12)：53-56.
[21]樊昌信,薛向阳.数字图像信号编码最新进展[J].电信科学.1993,9(4)：9-17.
[22]徐永军.小波分析及其在视频编码中的应用[J].山东电子.2004,(3)：52-55.
[23]谢永胜.数字图像拼接与配准技术的研究[D].杭州：杭州电子科技大学,2010.
[24]Skodras A, Christopoulos C, Ebrahimi T. Jpeg2000:the upcoming still image compression standard[J]. Pattern Recognition Letters.2001,22:1337-1345.
[25]Yu W, Sun F, Fritts J. Efficient rate control for jpeg-2000[J], IEEE Transactions on Circuits and Systems for Video Technology.2006,16:577-589.
[26]Pearlman W, Islam A, Nagaraj N, Said A. Efficient, low-complexity image coding with a set-partitioning embedded block coder[J]. IEEE Transactions on Circuits and Systems for Video Technology.2004,14:1219-1235.
[27]纪心毅.JPEG算法与矢量量化算法在图像压缩中的应用研究[D].合肥：合肥工业大学,2008.
[28]毕厚杰.新一代视频压缩编码标准.-H.264/AVC[M].北京：人民邮电出版社,2005：67.
[29]宋晓炜,杨蕾,王勇.一种基于HVS色度不敏感性的立体图像处理方法[J].中原工学院学报.2008,19(6)：49-52.
[30]Fouzi Douak, Redha Benzid, Nabil Benoudjit. Color image compression algorithm based on the DCT transform combined to an adaptive block scanning[J]. Int. J. Electron. Commun.2011,65:16-26.
[31]http://www.ibm.com/developerworks/cn/linux/l-cn-jpeg/index.html
[32]闫冰,张虹.静止图像编码方法[J].中小企业科技.2007,(6)：128-130.
[33]周乐.图像压缩技术JPEG与JPEG2000[J].四川兵工学报.2002,23(1)：21-22.
[34]潘远翠.基于图像压缩与编码技术的研究[J].数字技术与应用.2011,(4)：59-60.
[35]王娇JPEG2000编解码算法及优化研究[D].西安：西安电子科技大学,2009.
[36]http://jpkc.zust.edu.cn/2007/dmt/course/MMT08_05_6.htmz
[37]陈静.基于JPEG 2000的医学图像压缩研究[D].泰安：泰山医学院,2004.
[38]张鹤.基于四维n阶矩阵的彩色图像正交变换算法的研究[D].长春：吉林大学,2007.
[39]http://zh. wikipedia.org/wiki/MPEG
[40]王正勇,李永合MPEG-4与H.263视频编码性能比较[J].四川大学学报(自然科学版)2001,38(3)：366-369.
[41]刘书琴,毋立芳,宫玉.图像质量评价综述[J].中国科技论文在线.2011,6(7)：501-506.
[42]Dhara B, Chanda B. Color image compression based on block truncationcoding using pattern fitting principle[J]. Pattern Recognition.2007,40:2408-2417.
[43]奥本海姆.信号与系统(第二版)[M].西安：西安交通大学出版社,1998：124-127.
[44]古德曼.傅里叶光学导论[M].北京：电子工业出版社,2011：4-6.
[45]Maria Petrou, Panagiota Bosdogianni.数字图像处理疑难解析[M].北京：机械工业出版社,2005：50-51.
[46]朱艳秋,陈贺新,戴逸松.彩色图像三维矩阵变换压缩编码[J].电子学报.1997,25(7)：16-21.
[47]Li Li, Zhengxin Hou. Multiview Video Compression with 3D-DCT[J]. Information and Communications Technology,2007. ICICT 2007. ITI 5th International Conference on.2007:59-67
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