On-Line Visual Data Compression Along A One-Dimensional Scan

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Abstract
A new method for on-line visual data compression is presented, implementing nonuniform data selection according to gray-level neighborhood relations computed along a one-dimensional Hilbert scanning trajectory. Selection of a newly-scanned point (sample) is based on comparison of its gray level with a threshold determined by neighboring points previously scanned along the trajectory. Inherent in this algorithm is a mechanism for image pre-emphasis over areas (such as edges) exhibiting rapid changes in gray levels, whereas the reconstructed gray-level distribution over such areas is less accurate. Image reconstruction from the resultant (partial) subset of data is effected with the aid of a Zero-Order-Hold algorithm. At a rate of 0.38 bit/pixel obtained over a monochrome image of 512 by 512 pixels, the quality of the reconstructed image appears to be satisfactory, although it is not as good as that obtained with some of the best compression techniques, there is a clear advantage in using the proposed technique in cases where on-line processing and/or compression is important.

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