• DocumentCode
    1303153
  • Title

    Novel image compression method using edge-oriented classifier and novel predictive noiseless coding method

  • Author

    Lee, C.-H. ; Chen, L.-H.

  • Author_Institution
    Dept. of Inf. Sci., Chinese Culture Univ., Taipei, Taiwan
  • Volume
    144
  • Issue
    6
  • fYear
    1997
  • fDate
    12/1/1997 12:00:00 AM
  • Firstpage
    361
  • Lastpage
    368
  • Abstract
    A new image compression approach is proposed in which variable block size technique is adopted, using quadtree decomposition, for coding images at low bit rates. In the proposed approach, low-activity regions, which usually occupy large areas in an image, were coded with a larger block size and the block mean is used to represent each pixel in the block. To preserve edge integrity, the classified vector quantisation (CVQ) technique is used to code high-activity regions. A new edge-oriented classifier without employing any thresholds is proposed for edge classification. A novel predictive noiseless coding (NPNC) method which exploits the redundancy between neighbouring blocks is also presented to efficiently code the mean values of low-activity blocks and the addresses of edge blocks. The bit rates required for coding the mean values and addresses can be significantly reduced by the proposed NPNC method. Experimental results show that excellent reconstructed images and higher PSNR were obtained
  • Keywords
    edge detection; image classification; image coding; image reconstruction; prediction theory; quadtrees; vector quantisation; classified vector quantisation technique; edge integrity; edge-oriented classifier; high-activity regions; image compression method; low bit rates; low-activity regions; predictive noiseless coding method; quadtree decomposition; reconstructed images; redundancy; variable block size technique;
  • fLanguage
    English
  • Journal_Title
    Vision, Image and Signal Processing, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-245X
  • Type

    jour

  • DOI
    10.1049/ip-vis:19971326
  • Filename
    655605