RGB Image Compression Using Two Dimensional Discrete Cosine Transform

RGB Image Compression Using Two Dimensional Discrete Cosine Transform

  ijett-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2013 by IJETT Journal
Volume-4 Issue-4                       
Year of Publication : 2013
Authors : Vivek Arya , Dr. Priti Singh , Karamjit Sekhon

Citation 

Vivek Arya , Dr. Priti Singh , Karamjit Sekhon. "RGB Image Compression Using Two Dimensional Discrete Cosine Transform". International Journal of Engineering Trends and Technology (IJETT). V4(4):828-832 Apr 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract

To addresses the problem of reducing the memory space and amount of data required to represent a digital image. Image compression plays a crucial role in many important and adverse applications and including televideo conferencing, remote sensing, document, medical and facsimile transmission. The need for an efficient technique for compression of Images ever increasing because the raw images need large amounts of disk space seems to be a big disadvantage during transmission & storage. Even though there are so many compression technique already available - a better techn ique which is faster, memory efficient and simple surely suits the requirements of the user. In this paper the Spatial Redundancy method of image compression using a simple transform technique called Discrete Cosine Transform is proposed. This technique is simple in implementation and utilizes less memory. A software algorithm has been developed and implemented to compress the given RGB image using Discrete Cosine Transform techniques in a MATLAB platform. In this paper rgb image is compressed upto 70%, 60% , 40% and 20% and optimum results are obtained. The analysis of results obtain has been carried out with the help of MSE (mean square error) and PSNR (peak signal to noise ratio).

References

[1] R. C. Gonzalez, R. E. Woods, “Digital image processing,” Pearson Education, II I Edi tion, 2008
[2] David Salomon, “Data compression” spinger, Fourth Edition,2007
[3] Jiankun Li, Jin Li, and C. - C. Jay Kuo, “Layered DCT Still Image Compression”, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY , VOL. 7, NO. 2, pp. 440 - 443,APRIL 1997
[4] Zixiang Xiong, Kannan Ramchandran, Michael T. Orchard, and Ya - Qin Zhang,” A Comparative Study of DCT - and Wavelet - Based Image Coding”, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 9, NO. 5, pp. 692 - 695, AUGUST 1999
[5] Panos Nasiopoulos and Rabab K. Ward, “ A High - Quality Fixed - Length Compression Scheme for Color Images”, IEEE TRANSACTIONS ON COMMUNICATIONS, V OL. 43 , NO. 11, pp. 2672 - 2677, NOVEMBER 1995
[6] K. R. Rao and P. Yip, Discrete Cosine Transform . New York: Academic, 1990.
[7] J. M. Shapiro, “Embedded image coding using zerotrees of wavelet coefficients,” IEEE Trans. Signal Processing , vol. 41, pp. 3445 – 3463, Dec. 1993.
[8] A. Said and W. A. Pearlman, “A new, fast, and efficient image codec based on set partitioning in hierarchical trees,” IEEE Trans. Circuits Syst. Video Technol. , vol. 6, pp. 243 – 250, June 1996.
[9] D.Wu and E.C.Tan,“Comparison of loss less image compression”. TENCON 99 proceedings of the IEEE region 10 conference, Cheju island, South korea, vol.1, 1999, pages 718 - 721
[10] Jagadish H. Puj ar and Lohit M. Kadlaskar , “ A NEW LOSSLESS METHOD OF IMAGE COMPRESSION AND DECOMPRESSION USING HUFFMAN CODING TECHNIQUES ” JATIT, Edition, 2005 - 2010
[11] Lina J. Karam, “Handbook of image and video processing” Second Edition, 2005, Pages 643 - 660
[12] M. H. El Ayadi M. M. Syiam A. A. Gamgoum” A Comparative study of lossless image compression techniques” IJICIS, Vol. 5, No. 1, July 2005
[13] Chaur - Chin Chen, "On the selection of image compression algorithms," 14th International conference on pattern recognition (ICPR`98) - Volume 2, 1998.
[14] Amhamed saffor, Abdul Rahman Ramli, Kwan - Hoong Ng, “A Comparative study of Image Compression between JPEG and WAVELET”. Malaysian journal of computer science, vol. 14 no. 1, June 2001, Pages.39 - 45.
[15] Mr. T. Sreenivasulu reddy, Ms. K. Ramani, Dr. S. Varadarajan, Dr. B.C.Jinaga “Image compression using transform coding methods” , International journal of Computer science and network security, vol.7 no.7, July 2007.
[16] Andrew B. Watson” Image compression using the Discrete Cosine Transform” Mathematica journal, 4(1), 1994, Pages 81 - 88

Keywords
Image compression, DCT, IDCT, DCT2, IDCT2, MSE, PSNR, Redundancy.