• DocumentCode
    2869227
  • Title

    A space and frequency hybrid algorithm to remove block artifacts

  • Author

    Huang, Jiwu ; Shi, Yun Q.

  • Author_Institution
    Dept. of EE, Shantou Univ., Shantou, China
  • Volume
    2
  • fYear
    1998
  • fDate
    1998
  • Firstpage
    869
  • Abstract
    Postfiltering of block artifacts in decoded images has drawn extensive attention. But less improvements have been made for staircase noise. In this paper a space and frequency hybrid algorithm is presented. First, the edge information in the decoded images is extracted. Based on an analysis of artifacts in the frequency domain, the block effect in the edge image is removed by using a notch filter. The filtered edge image is used for a neighborhood analysis. A space-variant filter, consisting of a 2D LPF and a 1D directional LPF, is then applied to the decoded image to reduce artifacts. Which of the filters is chosen depends on the neighborhood analysis. Finally, the contrast is enhanced. The simulation results demonstrate that the proposed algorithm improves both the subjective visual quality and PSNR of decoded images effectively
  • Keywords
    decoding; edge detection; filtering theory; frequency-domain analysis; image coding; image enhancement; low-pass filters; notch filters; 1D directional LPF; 2D LPF; PSNR; block artifact removal; contrast enhancement; decoded images; edge extraction; frequency domain analysis; neighborhood analysis; notch filter; postfiltering; simulation; space-variant filter; space/frequency hybrid algorithm; staircase noise; subjective visual quality; Block codes; Data mining; Decoding; Filtering; Filters; Frequency domain analysis; Image analysis; Image edge detection; Pixel; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Proceedings, 1998. ICSP '98. 1998 Fourth International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-4325-5
  • Type

    conf

  • DOI
    10.1109/ICOSP.1998.770749
  • Filename
    770749