Lossless Geometry Compression for Floating-Point Data in Steady-State and Time-Varying Fields over Irregular Grids

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 applies to floating- point data without requiring an initial quantization step and is truly lossless. However, the technique works equally well even if quantization is performed. Moreover, it does not need any connectivity information, and 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.