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Algorithms for Lossless Compression in Image Processing Systems

Published: 10 November 2016 Publication History

Abstract

In this article, it is developed some area of issues related to data compression algorithms in the field of image processing. Image processing area is very commonly used today with multiple applications in different fields, but also, the image compression methods or algorithms for imaging are used every day by the computer users. This paper will highlight the result of reports over the investigations or comparisons on image compression methods and will provide conclusions and ideas for further research in this area, with intense uses. Today there are a lot of different data compression methodologies, which are used to compress different data formats like, video, audio, image files. This article represents a comparison of several compression methods based on previous research and the analysis in the context of their current needs. In conclusion, this topic combines image processing systems, the advantage of using parallel programming, the benefits and results of the image compression and also the importance of some fundamental algorithms in this area.

References

[1]
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, 9(8):1309-1324, 2000.
[2]
I. Tabus and J. Astola. Adaptive boolean predictive modelling with application to lossless image coding. In In SPIE - Statistical and Stochastic Methods for Image Processing II, pages 234--245, 1997.
[3]
A. J. Penrose and N. A. Dodgson. Error resilient lossless image coding. In In ICIP, Kobe, pages 426--429, 1999.
[4]
A. P. Neil. Extending Lossless Image Compression. PhD thesis, University of Cambridge, 2001.
[5]
Olivier Rioul and Martin Vetterli, "Wavelets and Signal Processing", IEEE Trans. on Signal Processing, Vol. 8, Issue 4, pp. 14--38 October 1991.
[6]
Subhasis Saha, "Image compression - from DCT to Wavelets- AReview"http://www.acm.org/crossroads/xrds63/sahaimcoding.html
[7]
A. Alice Blessie1, J. Nalini and S.C.Ramesh, "Image Compression Using Wavelet Transform Based on the Lifting Scheme and its Implementation", IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 3, No. 1, May 2011.
[8]
D. S. Taubman, "High performance scalable image compression with EBCOT", IEEE Transaction Image Processing, Vol. 9, No. 7, pp. 1158--1170, July 2000
[9]
M. Antonini, M. Barlaud, P. Mathieu, and I. Daubechies, "Image Coding Using Wavelet Transform," IEEE Trans. on Image Processing, Vol. 1, No.2, pp. 205--220, April 1992
[10]
"Wavelet filter evaluation for image compression". al., J. Liao et. August 1995, IEEE Trans. Image Process., Vol. 4, pp. 1053--1060
[11]
Priyanka Singh, Priti Singh, Rakesh Kumar Sharma "JPEG Image Compression based on Biorthogonal, Coiflets and Daubechies Wavelet Families", International Journal of Computer Applications (0975 - 8887) Volume 13- No.1, January 2011
[12]
S. W. Smith. The scientist and engineer's guide to digital signal processing. California Technical Publishing, San Diego, CA, USA, 1997.
[13]
G. Weinh, H. Stögner, and A. Uhl. Experimental study on lossless compression of biometric sample data. In Image and Signal Processing and Analysis, 2009. ISPA 2009., pages 517--522, 2009.
[14]
G. Schaefer, R. Starosolski, and S. Ying Zhu. An evaluation of lossless compression algorithms for medical infrared images, 2005.
[15]
G. Roelofs. PNG: The Definitive Guide. O'Reilly & Associates, Inc., Sebastopol, CA, USA, 1999.
[16]
D. Santa-Cruz and T. Ebrahimi. An Analytical Study of JPEG2000 Functionalities. In IEEE ICIP, pages 49--52, 2000.
[17]
D. Santa-Cruz, T. Ebrahimi, T. Ebrahimi A, J. Askelof, M. Larsson B, and C. A. Christopoulos B. JPEG2000 still image coding versus other standards. Howpublished = Public Draft FCD 14495, ISO / IEC JTC1 SC29 WG1 (JPEG / JBIG), 2000.
[18]
D. D. Shuai. Parallel lossless data compression: A particle dynamic approach. In Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues, ICIC '08, pages 266--274, 2008.

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cover image ACM Other conferences
PCI '16: Proceedings of the 20th Pan-Hellenic Conference on Informatics
November 2016
449 pages
ISBN:9781450347891
DOI:10.1145/3003733
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

  • Greek Com Soc: Greek Computer Society
  • TEI: Technological Educational Institution of Athens

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 November 2016

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Author Tags

  1. Data compression
  2. image processing
  3. lossless compression
  4. wavelet transform

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  • Short-paper
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PCI '16
PCI '16: 20th Pan-Hellenic Conference on Informatics
November 10 - 12, 2016
Patras, Greece

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Overall Acceptance Rate 190 of 390 submissions, 49%

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