A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
Dr. Dobb's Journal
Digital Image Compression Techniques
Digital Image Compression Techniques
Volume Data and Wavelet Transforms
IEEE Computer Graphics and Applications
Fast volume rendering of compressed data
VIS '93 Proceedings of the 4th conference on Visualization '93
Proceedings of the 7th conference on Visualization '96
Wavelet-based multiresolutional representation of computational field simulation datasets
VIS '97 Proceedings of the 8th conference on Visualization '97
TOPIC ISLANDS—a wavelet-based text visualization system
Proceedings of the conference on Visualization '98
Bicubic subdivision-surface wavelets for large-scale isosurface representation and visualization
Proceedings of the conference on Visualization '00
Wavelet representation of contour sets
Proceedings of the conference on Visualization '01
Structure-Significant Representation of Structured Datasets
IEEE Transactions on Visualization and Computer Graphics
AGP: Ocean Model Flow Visualization
IEEE Computer Graphics and Applications
Multiresolution and Adaptive Rendering Techniques for Structured, Curvilinear Data
Dagstuhl '97, Scientific Visualization
Multiresolutional Visualization of Evolving Distributed Simulations Using Wavelets and MPI
Dagstuhl '97, Scientific Visualization
Authenticity Analysis of Wavelet Approximations in Visualization
VIS '95 Proceedings of the 6th conference on Visualization '95
Case study: visualization of mesoscale flow features in ocean basins
VIS '94 Proceedings of the conference on Visualization '94
Web-based progressive geometry transmission using subdivision-surface wavelets
Web3D '05 Proceedings of the tenth international conference on 3D Web technology
A multi-resolution model of vector map data for rapid transmission over the Internet
Computers & Geosciences
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An important issue in scientific visualization systems is the management of data sets. Most data sets in scientific visualization, whether created by measurement or simulation, are usually voluminous. The goal of data management is to reduce the storage space and the access time of these data sets to speed up the visualization process. A new progressive transmission scheme using spline biorthogonal wavelet bases is proposed in this paper. By exploiting the properties of this set of wavelet bases, a fast algorithm involving only additions and subtractions is developed. Due to the multiresolutional nature of the wavelet transform, this scheme is compatible with hierarchical-structured rendering algorithms. The formula for reconstructing the functional values in a continuous volume space is given in a simple polynomial form. Lossless compression is possible, even when using floating-point numbers. This algorithm has been applied to data from a global ocean model. The lossless compression ratio is about 1.5:1. With a compression ratio of 50:1, the reconstructed data is still of good quality. Several other wavelet bases are compared with the spline biorthogonal wavelet bases. Finally, the reconstructed data is visualized using various algorithms and the results are demonstrated.