• DocumentCode
    3403146
  • Title

    An efficient lossless medical image transformation method by improving prediction model

  • Author

    Sepehrband, Farshid ; Mortazavi, Mohammad ; Ghorshi, Seyed

  • Author_Institution
    Sch. of Sci. & Eng., Sharif Univ. of Technol., Tehran, Iran
  • fYear
    2010
  • fDate
    24-28 Oct. 2010
  • Firstpage
    728
  • Lastpage
    731
  • Abstract
    Medical images include human body picture and it is used in diagnosis purpose. Lossless compression of medical image is an application of medical imaging. During lossless compression task, transformation algorithm can be used to increase compression ratio. In Real time applications such as telemedicine and online diagnosis, hardware implementation accelerates the process. Hence, for such purposes medical compression is better to be simple. Lossless JPEG and JPEG2000 are some compression method. JPEG2000 gives better compression ratio. However, it is complex. In this paper an efficient method of lossless image transformation has been introduced by improving prediction model. Simulation results show that the new method has reduced the entropy compared to Differential Pulse Code Modulation (DPCM) and Discrete Wavelet Transform (DWT) which are used in JPEG and JPEG2000 respectively. Moreover, this method is cost effective due to computational complexity and entropy reduction.
  • Keywords
    data compression; discrete wavelet transforms; image coding; medical image processing; pulse code modulation; JPEG2000; computational complexity; differential pulse code modulation; discrete wavelet transform; entropy reduction; human body picture; lossless JPEG; lossless compression; medical image transformation; online diagnosis; prediction model; telemedicine; Entropy; Image Transformation; JPEG standards; Lossless Compression; Medical Imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing (ICSP), 2010 IEEE 10th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-5897-4
  • Type

    conf

  • DOI
    10.1109/ICOSP.2010.5655764
  • Filename
    5655764