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Proceedings Paper

Arithmetic coding model for compression of LANDSAT images
Author(s): Arnulfo Perez; Sei-ichiro Kamata; Eiji Kawaguchi
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Paper Abstract

The compression of LANDSAT images using Hilbert or Peano scanning and adaptive arithmetic coding is considered. The Hilbert scan is a general technique for continuous scanning of multidimensional data. Arithmetic coding has established itself as the superior method for lossless compression. This paper extends on previous work on the integration of the arithmetic coding methodology and an n-dimensional Hilbert scanning algorithm developed by Perez, Kamata and Kawaguchi. Hilbert scanning preserves the spatial continuity of an image, on both the x and y directions, and a higher correlation exists between continuous points than in a raster scan. Therefore, a Hilbert adaptive scheme can better estimate the local probability distributions. Arithmetic coding is most efficient when the probabilities of the symbols are close to one. Therefore, by integrating both the spatial and spectral information into a unified context a high rate of compression can be achieved.

Paper Details

Date Published: 1 November 1991
PDF: 6 pages
Proc. SPIE 1605, Visual Communications and Image Processing '91: Visual Communication, (1 November 1991); doi: 10.1117/12.50281
Show Author Affiliations
Arnulfo Perez, Instituto Tecnologico y de Estudios Superiores de Monterrey (Mexico)
Sei-ichiro Kamata, Kyushu Institute of Technology (Japan)
Eiji Kawaguchi, Kyushu Institute of Technology (Japan)


Published in SPIE Proceedings Vol. 1605:
Visual Communications and Image Processing '91: Visual Communication
Kou-Hu Tzou; Toshio Koga, Editor(s)

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