Arithmetic coding model for compression of LANDSAT images

Arnulfo Perez; Sei-ichiro Kamata; Eiji Kawaguchi

doi:10.1117/12.50281

1 November 1991 Arithmetic coding model for compression of LANDSAT images

Arnulfo Perez, Sei-ichiro Kamata, Eiji Kawaguchi

Proceedings Volume 1605, Visual Communications and Image Processing '91: Visual Communication; (1991) https://doi.org/10.1117/12.50281
Event: Visual Communications, '91, 1991, Boston, MA, United States

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 a 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.

Citation Download Citation

Arnulfo Perez, Sei-ichiro Kamata, and Eiji Kawaguchi "Arithmetic coding model for compression of LANDSAT images", Proc. SPIE 1605, Visual Communications and Image Processing '91: Visual Communication, (1 November 1991); https://doi.org/10.1117/12.50281

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