Browse > Article
http://dx.doi.org/10.3837/tiis.2016.11.019

Improving JPEG-LS Performance Using Location Information  

Woo, Jae Hyeon (Graduate School of Information Security Korea University)
Kim, Hyoung Joong (Graduate School of Information Security Korea University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.10, no.11, 2016 , pp. 5547-5562 More about this Journal
Abstract
JPEG-LS is an international standard for lossless or near-lossless image-compression algorithms. In this paper, a simple method is proposed to improve the performance of the lossless JPEG-LS algorithm. With respect to JPEG-LS and its supplementary explanation, Golomb-Rice (GR) coding is mainly used for entropy coding, but it is not used for long codewords. The proposed method replaces a set of long codewords with a set of shorter location map information. This paper shows how efficiently the location map guarantees reversibility and enhances the compression rate in terms of performance. Experiments have also been conducted to verify the efficiency of the proposed method.
Keywords
JPEG-LS; Lossless compression; Golomb code; Golomb-Rice; Location map;
Citations & Related Records
연도 인용수 순위
  • Reference
1 N. Merhav, G. Seroussi, and M.J. Weinberger, "Optimal Prefix Codes for Sources with Two-Sided Geometric Distributions," IEEE Transactions on Information Theory, vol. 46, no. 1, pp. 120-135, Jan. 2000.
2 S. A. Martucci, "Reversible compression of HDTV images using median adaptive prediction and arithmetic coding," in Proc. of IEEE International Symposium on Circuits and Systems, pp.1310-1313, 1990.
3 S. W. Golomb, "Run Length Encodings," IEEE Transactions on Information Theory, vol. 12, pp. 399-401, 1966.   DOI
4 R. F. Rice, "Practical Universal Noiseless Coding," in Proc. of SPIE 0207, Applications of Digital Image Processing III, 247, 1979.
5 V. P. Baligar, L. M. Patnaik, and G. R. Nagabhushana, "High compression and low order linear predictor for lossless coding of grayscale images," Image and Vision Computing, vol. 21, pp. 543-550, 2003.   DOI
6 S. Bedi, E. A. Edirisinghe, and G. Grecos, "Improvements to the JPEG-LS prediction scheme," Image and Vision Computing, vol. 22, pp. 9-14, Sep. 2004.   DOI
7 K. Horvath, H. Stogner, and G. Weinhandel, "Experimental study on lossless compression of biometric iris data," in Proc. of the 7th International Symposium on Image and Signal Processing and Analysis, pp. 379-384, Sep. 2011.
8 A. Khademi and S Krishnan, "Comparison of JPEG 2000 and other lossless compression schemes for digital mammograms," in Proc. of 27th Annual International Conference of the Engineering in Medicine and Biology Society, pp. 3771-3774, Jan. 2006.
9 J. Kim and C. M. Kyung, "A lossless embedded compression using significant bit truncation for HD video coding," IEEE Transactions on Circuits and Systems for video technology, vol. 20, no. 6, Jun. 2010.
10 J. Rissanen and G. G. Langdon, Jr, "Universal modeling and coding," IEEE Transactions on Information Theory, vol. 27, pp. 12-23, Jan. 1981.   DOI
11 G. Deng, H. Ye, and L. Cahill, "Adaptive techniques for lossless data compression," in Proc. of the Australia and New Zealand Conference on Intelligent Information Systems, pp. 345-350, 2001.
12 A. Martchenko and G. Deng, "Bayesian predictor combination for lossless image compression," IEEE Transactions on Image Processing, vol.22, pp.5263-5270, 2013.   DOI
13 A. Masmoudi, W. Puech, and A. Masmoudi, "An improved lossless image compression based arithmetic coding using mixture of non-parametric distributions," Multimedia Tools and Applications, vol. 74, no. 23, pp. 10605-10619, 2015.   DOI
14 S. Zhao, Y. Xu, H. Li, and H. Yang, "A comparison of lossless compression methods for palmprint images," Journal of Software, vol. 7, no. 3, pp.594-598, Mar. 2012.
15 T. Starosolski, "Simple fast and adaptive lossless image compression algorithm," Software: Practice and Experience, vol. 37, no. 1, pp. 65-91, Jan. 2007.   DOI
16 X. Wu and N. Memon, "Context-based, adaptive, lossless image codec," IEEE Transactions on Communications, vol. 45, no. 4, pp. 437-444, Apr. 1997.   DOI
17 J. Tian, "Reversible data embedding using a difference expansion," IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, no. 8, pp. 890-896, Aug. 2003.   DOI
18 B. G. Mobasseri, R. J. Berger, M. P. Marcinak, and Y. J. NaikRaikar, "Data embedding in JPEG bitstream by code mapping," IEEE Transactions on Image Processing, vol. 19, no. 4, pp. 958-966, Apr. 2010.   DOI
19 Z. Qian and X. Zhang, "Lossless data hiding in JPEG bitstream," Journal of Systems and Software, vol. 85, no. 2, pp. 309-313, Feb. 2012.   DOI
20 J. J. Ding, W. Y. Wei, and G. C. Pan, "Modified Golomb coding algorithm for asymmetric two-sided geometric distribution data," in Proc. of The 20th European Signal Processing Conference, pp.1548-1552, 2012.
21 http://imagecompression.info/test_images
22 Z. Ni, Y.-Q. Shi, and N. Ansari, "Reversible data hiding," IEEE Transactions on Circuits and Systems for Video Technology, vol. 16, no. 3, pp. 354-362, Mar. 2006.   DOI
23 H .J. Kim, V. Sachnev, Y. Q. Shi, J. Nam, and H. G. Choo, "A novel difference expansion transform for reversible data embedding," IEEE Transactions on Information Forensics and Security, vol. 3, no. 3, pp. 1147-1156, Sep. 2008.
24 http://links.uwaterloo.ca/Repository.html
25 http://www.stat.columbia.edu/-jakulin/jpeg-ls/mirror.htm
26 M. J. Weinberger, G. Seroussi, and G. Sapiro, "The LOCO-I lossless image compression algorithm: Principles and standardization into JPEG-LS," IEEE Transactions on Image Processing, vol. 9, no. 8, pp. 1309-1324, Aug. 2000.   DOI
27 http://kr.mathworks.com/matlabcentral/fileexchange/53039-jpegls-codec