• DocumentCode
    2851788
  • Title

    Image compression with geometrical wavelets

  • Author

    Le Pennec, E. ; Mallat, Stephane

  • Author_Institution
    Centre de Math. Appliquees, Ecole Polytech., Palaiseau, France
  • Volume
    1
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    661
  • Abstract
    We introduce a sparse image representation that takes advantage of the geometrical regularity of edges in images. A new class of one-dimensional wavelet orthonormal bases, called foveal wavelets, are introduced to detect and reconstruct singularities. Foveal wavelets are extended in two dimensions, to follow the geometry of arbitrary curves. The resulting two dimensional “bandelets” define orthonormal families that can restore close approximations of regular edges with few non-zero coefficients. A double layer image coding algorithm is described. Edges are coded with quantized bandelet coefficients, and a smooth residual image is coded in a standard two-dimensional wavelet basis
  • Keywords
    data compression; edge detection; geometric codes; image coding; image representation; transform coding; wavelet transforms; 2D wavelet basis; arbitrary curves; double layer image coding algorithm; foveal wavelets; geometrical regularity; geometrical wavelets; image compression; nonzero coefficients; one-dimensional wavelet orthonormal bases; quantized bandelet coefficients; regular edges; singularities detection; singularities reconstruction; smooth residual image; sparse image representation; two dimensional bandelets; Code standards; Continuous wavelet transforms; Geometry; Image coding; Image edge detection; Image reconstruction; Image representation; Image restoration; Rate distortion theory; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2000. Proceedings. 2000 International Conference on
  • Conference_Location
    Vancouver, BC
  • ISSN
    1522-4880
  • Print_ISBN
    0-7803-6297-7
  • Type

    conf

  • DOI
    10.1109/ICIP.2000.901045
  • Filename
    901045