Science Journal of Education

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Medical Image Compression Using DEFLATE Algorithm

Received: 16 May 2015    Accepted: 18 May 2015    Published: 01 June 2015
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Abstract

Lossless image compression has one of its important applications in the field of medical images. Efficient storage, transmission, management and retrieval of the huge data produced by the medical images have nowadays become very much complex. The solution to this complex problem lies in the lossless compression of the medical images. The medical data is compressed in such a way so that no medical information is lost. The super spatial structure prediction algorithm is used to find the optimal prediction of structured components in an image. The block matching is achieved using inverse diamond search algorithm. And finally LZ8 algorithm is applied to achieve the higher compression ratio of the medical images.

DOI 10.11648/j.sjedu.s.2015030401.14
Published in Science Journal of Education (Volume 3, Issue 4-1, August 2015)

This article belongs to the Special Issue Science Learning in Higher Education

Page(s) 17-20
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Super spatial Structure Prediction, Inverse Diamond Search, LZ8

References
[1] X. Wu and N. Memon, ”Context-based adaptive lossless image coding”, IEEE Trans. Commun, vol 45.no.4,pp 437-444, Apr 1997.
[2] Abdesh Singla, Kulbhushan Singla. A, “New lossless compression scheme for medical images”, EXCEL International Journal of Multidisciplinary Management Studies (EIJMMS) Vol.3 (7) July (2013).
[3] M. Moorthi, Dr. Amudha, “A near lossless compression method for medical images”, IEEE-International Conference on Advances in Engineering, Science and Management (ICAESM-2012) March30, 2012.
[4] Smitha Joyce Pinto, Jayanand P Gawande, “Performance analysis of medical image compression techniques”, IEEE Transaction on image processing, (2012).
[5] S. Zhu and K.K. Ma, ‘A New diamond search algorithm for fast block matching motion estimation”, IEEE Trans. Image Process.,9: 287-290,2000.
[6] L. M. Po, C.W. Ting, K. M. Wong and K. H. Ng,” Novel point-oriented inner searches for fast block motion estimation”, IEEE Trans. Multimedia,9:9-15,2007.
[7] P. Franti,” A Fast and Efficient Compression Method for Binary Images”,1993.
[8] B .Brindha, G. Raghuraman, “Region based lossless compression for digital images in telemedicine application”, International conference on Communication and Signal Processing, April (2013).
[9] P. Sudha , “Image compression with scalable ROI using adaptive huffman coding”, IJCSMC, Vol. 2, Issue.4 (2012).
[10] R. Rajeshwari and R. Rajesh, “WBMP Compression”, International journal of Wisdom Based Computing, vol.1, No.2, 2011.
Author Information
  • Department of CSE, St. Joseph College of Engineering and Technology, Dar es Salaam, United Republic of Tanzania

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  • APA Style

    L. Nirmal Jega Selvi. (2015). Medical Image Compression Using DEFLATE Algorithm. Science Journal of Education, 3(4-1), 17-20. https://doi.org/10.11648/j.sjedu.s.2015030401.14

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    ACS Style

    L. Nirmal Jega Selvi. Medical Image Compression Using DEFLATE Algorithm. Sci. J. Educ. 2015, 3(4-1), 17-20. doi: 10.11648/j.sjedu.s.2015030401.14

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    AMA Style

    L. Nirmal Jega Selvi. Medical Image Compression Using DEFLATE Algorithm. Sci J Educ. 2015;3(4-1):17-20. doi: 10.11648/j.sjedu.s.2015030401.14

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  • @article{10.11648/j.sjedu.s.2015030401.14,
      author = {L. Nirmal Jega Selvi},
      title = {Medical Image Compression Using DEFLATE Algorithm},
      journal = {Science Journal of Education},
      volume = {3},
      number = {4-1},
      pages = {17-20},
      doi = {10.11648/j.sjedu.s.2015030401.14},
      url = {https://doi.org/10.11648/j.sjedu.s.2015030401.14},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.sjedu.s.2015030401.14},
      abstract = {Lossless image compression has one of its important applications in the field of medical images. Efficient storage, transmission, management and retrieval of the huge data produced by the medical images have nowadays become very much complex. The solution to this complex problem lies in the lossless compression of the medical images. The medical data is compressed in such a way so that no medical information is lost. The super spatial structure prediction algorithm is used to find the optimal prediction of structured components in an image. The block matching is achieved using inverse diamond search algorithm. And finally LZ8 algorithm is applied to achieve the higher compression ratio of the medical images.},
     year = {2015}
    }
    

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