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Proceedings Paper

Space-filling curves for image compression
Author(s): Baback Moghaddam; Kenneth J. Hintz; Clayton V. Stewart
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Paper Abstract

This paper outlines the use of space-filling curves in transform image compression. Specifically, a space-filling Hilbert curve is used for mapping the two-dimensional image into a suitable one-dimensional representation. Compared to simple raster-scans, this topological mapping is spatially non-disruptive and tends to preserve local pixel correlations in the original two-dimensional image. Standard transform coefficient reduction and coding techniques can then be applied to the one-dimensional representation for the purposes of data compression. The advantages of the one-dimensional coding, in terms of computational cost and subjective image quality, are also discussed.

Paper Details

Date Published: 1 August 1991
PDF: 8 pages
Proc. SPIE 1471, Automatic Object Recognition, (1 August 1991); doi: 10.1117/12.44897
Show Author Affiliations
Baback Moghaddam, George Mason Univ. (United States)
Kenneth J. Hintz, George Mason Univ. (United States)
Clayton V. Stewart, George Mason Univ. (United States)


Published in SPIE Proceedings Vol. 1471:
Automatic Object Recognition
Firooz A. Sadjadi, Editor(s)

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