• DocumentCode
    2737796
  • Title

    Wavelet based image compression methods — State of the art

  • Author

    Selvakumarasamy, K. ; Poornachandra, S.

  • Author_Institution
    Anna Univ. of Technol., Chennai, India
  • fYear
    2012
  • fDate
    26-28 July 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    With the increasing growth of technology and the entrance into the digital world, we have to handle a enormous amount of information every time which often presents difficulties. So, the digital information must be stored and retrieved in a professional and valuable manner, in order for it to be put to practical use. Imaging requires large amount of memory to store the digitized data. Due to the transmission bandwidth constraint, images must be compressed before transmission and storage. The wavelet transform is more and more widely used in image processing algorithms. In this paper, we reviewed the different methods of image coding. We reviewed the different methods in terms of PSNR [Peak Signal to Noise Ratio] and MSE [Mean Square Error] which can be used to better understand the relationship between various methods and their features.
  • Keywords
    data compression; image coding; mean square error methods; wavelet transforms; MSE; PSNR; digital information retrieval; digital information storage; image coding; image compression method; mean square error; peak signal to noise ratio; wavelet transform; Biomedical imaging; Encoding; Image coding; Image resolution; Indexes; PSNR; Partitioning algorithms; ASWDR; EZW; LSK; LZW; NLS; SPECK; SPIHT;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing Communication & Networking Technologies (ICCCNT), 2012 Third International Conference on
  • Conference_Location
    Coimbatore
  • Type

    conf

  • DOI
    10.1109/ICCCNT.2012.6396077
  • Filename
    6396077