• DocumentCode
    1595577
  • Title

    Highly Accurate Distortion Estimation for JPEG2000 through PDF-Based Estimators

  • Author

    Auli-Llinas, Francesc ; Marcellin, Michael W. ; Serra-Sagrista, J.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Arizona, Tucson, AZ
  • fYear
    2009
  • Firstpage
    391
  • Lastpage
    400
  • Abstract
    Distortion estimation techniques are often employed in bitplane coding engines to minimize the computational load, or the memory requirements, of the encoder. A common approach is to determine distortion estimators that approximate the mean squared error decreases when data are successively coded and transmitted. Such estimators usually assume that coefficients are uniformly distributed in the quantization interval. Even though this assumption simplifies estimation, it does not exactly correspond with the nature of the signal. This work introduces new distortion estimators determined through a precise approximation of the coefficient´s distribution within the quantization intervals. Experimental results obtained when our estimators are used for the post-compression rate-distortion optimization process of JPEG2000 suggest that they are able to approximate distortion with very high accuracy.
  • Keywords
    data compression; image coding; mean square error methods; optimisation; JPEG2000; bitplane coding engines; distortion estimation; image coding; mean squared error; pdf-based estimators; post-compression rate-distortion optimization process; Data compression; Data engineering; Decoding; Engines; Image coding; Image reconstruction; Quantization; Rate-distortion; Transform coding; Wavelet coefficients; Distortion estimators; JPEG2000; rate-distortion optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Compression Conference, 2009. DCC '09.
  • Conference_Location
    Snowbird, UT
  • ISSN
    1068-0314
  • Print_ISBN
    978-1-4244-3753-5
  • Type

    conf

  • DOI
    10.1109/DCC.2009.20
  • Filename
    4976483