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Proceedings Paper

Coding of surveillance imagery for interpretability using local dimension estimates
Author(s): Robert Prandolini
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Paper Abstract

This paper introduces a novel image coding principle: the coding of an image to maximize its interpretability versus bit-rate performance. For large surveillance images it would be more appropriate if the encoded wavelet coefficients were prioritized in their order of importance for interpretability. This paper presents one method for such a system. The importance values are derived from the estimates of the local dimension in image regions, which is a measure on the local image dynamics. The scale of the area used for the estimates is dyadic and maps to the image scale-space. The wavelet coefficients from a Mallat decomposition are prioritized according to their importance, based on the local information dimension estimates. Subjective evaluations have shown that this importance prioritization schema is preferred over the traditional progressive PSNR optimal approach. The paper will discuss the implementation of an importance prioritization schema for the EBCOT image coder, which is the algorithm used in JPEG2000. The concept of importance prioritization for interpretability may benefit future low bit-rate image and video coding.

Paper Details

Date Published: 30 May 2000
PDF: 11 pages
Proc. SPIE 4067, Visual Communications and Image Processing 2000, (30 May 2000); doi: 10.1117/12.386586
Show Author Affiliations
Robert Prandolini, Defence Science and Technology Organisation (Australia)


Published in SPIE Proceedings Vol. 4067:
Visual Communications and Image Processing 2000
King N. Ngan; Thomas Sikora; Ming-Ting Sun, Editor(s)

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