• DocumentCode
    573201
  • Title

    Efficiency evaluation of different wavelets for image compression

  • Author

    Benchikh, Salam ; Corinthios, Michael

  • Author_Institution
    Dept. of Electr. Eng., Ecole Polytech. de Montreal, Montreal, QC, Canada
  • fYear
    2012
  • fDate
    2-5 July 2012
  • Firstpage
    1420
  • Lastpage
    1421
  • Abstract
    In this paper, application to image processing and image compression using the discrete wavelet transform (DWT) is presented. We show the impact of the spectral distribution of the images on the quality of the image compression technique. Four families of wavelets are considered: 1) Bi-orthogonal, 2) Daubechies, 3) Coiflet and 4) Symlet. Since the good basis wavelet recommended for DWT compressor may depend on the choice of test images, we consider three test images with different but moderate spectral activities. We then evaluate the performance of the four wavelets families on each test image. A comparative results for several wavelets used in DWT compression techniques are presented using the peak signal to noise ratio (PSNR) and compression ratio (CR) as a measure of quality. Finally, we present the comparative result according to PSNR versus CR for four families of wavelets, showing that bior4.4 yields a better performance than the other Wavelets in terms of tradeoff between PSNR and CR.
  • Keywords
    data compression; discrete wavelet transforms; image coding; CR; Coiflet wavelets; DWT compression techniques; Daubechies wavelets; PSNR; Symlet wavelets; bior4.4; biorthogonal wavelets; compression ratio; discrete wavelet transform; image compression; image processing; peak signal to noise ratio; spectral image distribution; wavelet evaluation; Biomedical imaging; Computers; Discrete wavelet transforms; Image coding; Transform coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science, Signal Processing and their Applications (ISSPA), 2012 11th International Conference on
  • Conference_Location
    Montreal, QC
  • Print_ISBN
    978-1-4673-0381-1
  • Electronic_ISBN
    978-1-4673-0380-4
  • Type

    conf

  • DOI
    10.1109/ISSPA.2012.6310520
  • Filename
    6310520