A quadtree dictionary approach to multi-resolution compression

Authors:
Rion Dooley
Affiliations:
Louisiana State University, Baton Rouge, LA
Venue:
ACM-SE 42 Proceedings of the 42nd annual Southeast regional conference
Year:
2004

Citing 7
Cited 0

Multidimensional access methods

ACM Computing Surveys (CSUR)
Coarse-Grained Parallel Algorithms for Multi-DimensionalWavelet Transforms

The Journal of Supercomputing
Statistical Pattern Recognition: A Review

IEEE Transactions on Pattern Analysis and Machine Intelligence
A hierarchical error controlled octree data structure for large-scale visualization

Crossroads
Wavelets for Computer Graphics: A Primer, Part 1

IEEE Computer Graphics and Applications
Load Adaptive Algorithms and Implementations for the 2D Discrete Wavelet Transform on Fine-Grain Multithreaded Architectures

IPPS '99/SPDP '99 Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing
A Distributed Quadtree Dictionary Approach to Multi-Resolution Compression

ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2

Quantified Score

Hi-index	0.00

Visualization

Abstract

As we attempt to harness the power of tomorrow's mobile devices, intelligent information delivery becomes a primary concern. Getting the appropriate data to the resources that need it is referred to as the needs mismatch problem. In this paper we present a lossless multi-resolution compression technique based on a quadtree dictionary (QTD) that achieves 8:1 compression in the worst case. Test results show our method improves upon probabilistic, wavelet, and tree reduction techniques while providing 54:1 compression in the average case.