Self-Describing Context-Based Pixel Ordering.

Autor: Bebis, George, Boyle, Richard, Koracin, Darko, Parvin, Bahram, Itani, Abdul, Das, Manohar
Zdroj: Advances in Visual Computing; 2005, p413-419, 7p
Abstrakt: In this paper we introduce a novel self-describing context-based pixel ordering for digital images. Our method is inherently reversible and uses the pixel value to guide the exploration of the two-dimensional image space, in contrast to universal scans where the traversal is based solely on the pixel position. The outcome is a one-dimensional representation of the image with enhanced autocorrelation. When used as a front-end to a memoryless entropy coder, empirical results show that our method, on average, improves the compression rate by 11.56% and 5.23% compared to raster-scan and Hilbert space-filling curve, respectively. [ABSTRACT FROM AUTHOR]
Databáze: Supplemental Index