• DocumentCode
    1035827
  • Title

    Enhancing Poisson´s Equation-Based Approach for DCT Prediction

  • Author

    Lakhani, G.

  • Author_Institution
    Texas Tech. Univ., Lubbock
  • Volume
    17
  • Issue
    3
  • fYear
    2008
  • fDate
    3/1/2008 12:00:00 AM
  • Firstpage
    427
  • Lastpage
    430
  • Abstract
    Yamatani and Saito recently published an interesting method for predicting discrete cosine transform (DCT) coefficients of an image block, which uses partial derivatives of the image at the block boundary points. It estimates partial derivatives the same way for all four side boundary points. In this correspondence, we improve their estimation method for the left and top side boundary points by observing that the decoder can use 1-D DCT of the rightmost column of pixels of the block on the left side and bottom row pixels of the block on the top side instead of using just the DC of these two blocks. It led us to revise their prediction equations. Experimental results show that the cumulative reduction in the size of the first five AC coefficients obtained using their equations is 15.1%, and the same using our equations is 24.6%.
  • Keywords
    Poisson equation; discrete cosine transforms; image processing; DCT prediction; Poisson equation; block boundary points; cumulative reduction; discrete cosine transform coefficients; estimation method; image block; partial derivatives; DCT prediction; Discrete cosine transform (DCT); JPEG; Poisson´s equation; Algorithms; Computer Graphics; Computer Simulation; Data Compression; Data Interpretation, Statistical; Image Enhancement; Image Interpretation, Computer-Assisted; Models, Statistical; Poisson Distribution; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2007.915560
  • Filename
    4431869