Geometric compression through topological surgery
ACM Transactions on Graphics (TOG)
Tetrahedral mesh compression with the cut-border machine
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Progressive geometry compression
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
On-the-Fly rendering of losslessly compressed irregular volume data
Proceedings of the conference on Visualization '00
Geometric compression for interactive transmission
Proceedings of the conference on Visualization '00
Introduction to algorithms
Progressive lossless compression of arbitrary simplicial complexes
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Compressing polygon mesh geometry with parallelogram prediction
Proceedings of the conference on Visualization '02
Edgebreaker: Connectivity Compression for Triangle Meshes
IEEE Transactions on Visualization and Computer Graphics
Optimal Alphabet Partitioning for Semi-Adaptive Coding of Sources of Unknown Sparse Distributions
DCC '03 Proceedings of the Conference on Data Compression
Compressing Hexahedral Volume Meshes
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
Out-of-core compression for gigantic polygon meshes
ACM SIGGRAPH 2003 Papers
Optimized Prediction for Geometry Compression of Triangle Meshes
DCC '05 Proceedings of the Data Compression Conference
Universal coding, information, prediction, and estimation
IEEE Transactions on Information Theory
Lossless image compression with a codebook of block scans
IEEE Journal on Selected Areas in Communications
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In this paper we investigate the problem of lossless geometry compression of irregular-grid volume data represented as a tetrahedral mesh. We propose a novel lossless compression technique that effectively predicts, models, and encodes geometry data for both steady-state (i.e., with only a single time step) and time-varying datasets. Our geometry coder is truly lossless and also does not need any connectivity information. Moreover, it can be easily integrated with a class of the best existing connectivity compression techniques for tetrahedral meshes with a small amount of overhead information. We present experimental results which show that our technique achieves superior compression ratios, with reasonable encoding times and fast (linear) decoding times.