• DocumentCode
    2875177
  • Title

    Hilbert scan and image compression

  • Author

    Biswas, Sambhunath

  • Author_Institution
    Machine Intelligence Unit, Indian Stat. Inst., Calcutta, India
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    207
  • Abstract
    The use of the Hilbert scan is relatively new in image compression. This scan is guided by the Hilbert space filling curve. A Hilbert image, thus produced by this scan of a gray level image provides better compression rate than that of a raster scanned image. Since a Hilbert image is a 1D image, an efficient 1D algorithm based on a Bezier-Bernstein polynomial has been developed to simultaneously separate out and and approximate homogeneous segments of pixels depending on some absolute error based criteria. The approximation parameters are then encoded by a Huffman coding scheme. Investigation shows that better performance on image compression can be achieved using the Hilbert scan. Comparison with an existing algorithm shows also better performance of the proposed algorithm
  • Keywords
    Huffman codes; approximation theory; data compression; image coding; polynomials; 1D image; Bezier-Bernstein polynomial; Hilbert image; Hilbert scan; Hilbert space filling curve; Huffman coding scheme; absolute error based criteria; compression rate; gray level image; image compression; Filling; Hilbert space; Huffman coding; Image coding; Image processing; Image resolution; Image segmentation; Machine intelligence; Pixel; Polynomials;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2000. Proceedings. 15th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-0750-6
  • Type

    conf

  • DOI
    10.1109/ICPR.2000.903522
  • Filename
    903522