Space-filling curves for image compression

Baback Moghaddam; Kenneth J. Hintz; Clayton V. Stewart

doi:10.1117/12.44897

1 August 1991 Space-filling curves for image compression

Baback Moghaddam, Kenneth J. Hintz, Clayton V. Stewart

Proceedings Volume 1471, Automatic Object Recognition; (1991) https://doi.org/10.1117/12.44897
Event: Orlando '91, 1991, Orlando, FL, United States

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.

Citation Download Citation

Baback Moghaddam, Kenneth J. Hintz, and Clayton V. Stewart "Space-filling curves for image compression", Proc. SPIE 1471, Automatic Object Recognition, (1 August 1991); https://doi.org/10.1117/12.44897

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