Share Email Print

Journal of Electronic Imaging

Lossless image compression via bit-plane separation and multilayer context tree modeling
Author(s): Alexey Podlasov; Pasi Franti
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Color separation and highly optimized context tree modeling for binary layers have provided the best compression results for color map images that consist of highly complex spatial structures but only a relatively few number of colors. We explore whether this kind of approach works on photographic and palette images as well. The main difficulty is that these images can have a much higher number of colors, and it is therefore much more difficult to exploit spatial dependencies via binary layers. The original contributions of this work include: 1. the application of context-tree-based compression (previously designed for map images) to natural and color palette images; 2. the consideration of four different methods for bit-plane separation; and 3. Extension of the two-layer context to a multilayer context for better utilization of the crosslayer correlations. The proposed combination is extensively compared to state of the art lossless image compression methods.

Paper Details

Date Published: 1 October 2006
PDF: 11 pages
J. Electron. Imaging. 15(4) 043009 doi: 10.1117/1.2388255
Published in: Journal of Electronic Imaging Volume 15, Issue 4
Show Author Affiliations
Alexey Podlasov, Joensuu Yliopisto (Finland)
Pasi Franti, Joensuun Yliopisto (Finland)

© SPIE. Terms of Use
Back to Top