• DocumentCode
    3528790
  • Title

    A novel approach to color image compression using 3-d Discrete Cosine Transform (DCT)

  • Author

    Nath, V.K. ; Hazarika, D. ; Mahanta, A.

  • Author_Institution
    Deptt. Of Electron.&Commun. Eng.., Tezpur Univ., Tezpur
  • fYear
    2008
  • fDate
    16-19 Oct. 2008
  • Firstpage
    205
  • Lastpage
    210
  • Abstract
    Most of the color image compression schemes transforms the highly correlated RGB color space into a decorrelated color space like YUV, YCrCb etc. in order to reduce the redundancies between the color components, then the decorrelated color components are coded individually by monochrome image compression schemes. In this paper, we present a novel approach to color image compression scheme using 3-Dimensional Discrete Cosine Transform (3-D DCT). We use 3-D DCT to reduce the intercolor redundancy. In the proposed scheme the 3-D block DCT is directly applied on the highly correlated RGB color components and the coefficients are quantized and entropy coded. We also propose a wavelet structure for 3-D block DCT coefficients. We use Lagrange multiplier method for optimal bit allocation between the different slices of 3-D DCT coefficients. Our proposed coder gains competitive results comparing to the performance of JPEG baseline and JPEG2000 standard. Experimental results shows that the proposed coder performs close to the JPEG2000 standard in terms of R-D performance and outperforms the JPEG baseline standard by a large margin.
  • Keywords
    data compression; discrete cosine transforms; entropy; image coding; quantisation (signal); 3D discrete cosine transform; Lagrange multiplier method; color image compression; correlated RGB color; entropy coded; intercolor redundancy reduction; optimal bit allocation; quantised signal; Bit rate; Code standards; Color; Decorrelation; Discrete cosine transforms; Discrete transforms; Entropy; Image coding; Lagrangian functions; Performance gain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning for Signal Processing, 2008. MLSP 2008. IEEE Workshop on
  • Conference_Location
    Cancun
  • ISSN
    1551-2541
  • Print_ISBN
    978-1-4244-2375-0
  • Electronic_ISBN
    1551-2541
  • Type

    conf

  • DOI
    10.1109/MLSP.2008.4685480
  • Filename
    4685480