Information

Abstract

2D wavelets are usually generated from 1D wavelets through the rectangular or through the square decomposition scheme. In this paper a new adaptive 2D decomposition scheme for compression related applications is presented. The adaptive 2D decomposition selects 2D wavelet functions based on the compression of the coefficients, but needs only the same number of 1D filter operations as the rectangular decomposition for the compression and even less for the decompression. Results for lossless image compression have shown improvements in the compression rate between 1% and 10% compared to the square decomposition. Only in the case of very small images (below 50x50) the adaptive decomposition was outperformed by the square decomposition because of the overhead to store the selection, which 2D wavelets should be used.

Additional Files and Images

Weblinks

No further information available.

BibTeX

@techreport{Kopp-1995-LWB,
  title =      "Lossless Wavelet Based Image Compression with Adaptive 2D   
                             Decomposition",
  author =     "Manfred Kopp",
  year =       "1995",
  abstract =   "2D wavelets are usually generated from 1D wavelets through
               the rectangular or through the square decomposition scheme.
               In this paper a new adaptive 2D decomposition scheme for
               compression related applications is presented. The adaptive
               2D decomposition selects 2D wavelet functions based on the
               compression of the coefficients, but needs only the same
               number of 1D filter operations as the rectangular
               decomposition for the compression and even less for the
               decompression. Results for lossless image compression have
               shown improvements in the compression rate between 1% and
               10% compared to the square decomposition. Only in the case
               of very small images (below 50x50) the adaptive
               decomposition was outperformed by the square decomposition
               because of the overhead to store the selection, which 2D
               wavelets should                 be used.",
  month =      nov,
  number =     "TR-186-2-95-11",
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  institution = "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  note =       "human contact: technical-report@cg.tuwien.ac.at",
  keywords =   "image compression, wavelets, adaptive 2D wavelet
               decomposition",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/1995/Kopp-1995-LWB/",
}