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Characterization of Signals from Multiscale Edges
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Vector quantization for volume rendering
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Second generation compact image coding with wavelets
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Image analysis with two-dimensional continuous wavelet transform
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Lossless compression of volume data
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A multiresolution framework for volume rendering
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Multiresolution support applied to image filtering and restoration
Graphical Models and Image Processing
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Wavelet-based multiresolutional representation of computational field simulation datasets
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Volume Rendering of DCT-Based Compressed 3D Scalar Data
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Multiscale Volume Representation by a DoG Wavelet
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A Multiscale Model for Structure-Based Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
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Volume Data and Wavelet Transforms
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Direct Rendering of Laplacian Pyramid Compressed Volume Data
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High-Speed Volume Rendering Using Redundant Block Compression
VIS '95 Proceedings of the 6th conference on Visualization '95
Analysis, control and evaluation of image generation in volume rendering
Analysis, control and evaluation of image generation in volume rendering
Progressive transmission of scientific data using biorthogonal wavelet transform
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A new, fast, and efficient image codec based on set partitioning in hierarchical trees
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Feature based volumetric video compression for interactive playback
VVS '02 Proceedings of the 2002 IEEE symposium on Volume visualization and graphics
Interactive rendering of large volume data sets
Proceedings of the conference on Visualization '02
Spatial Domain Wavelet Design for Feature Preservation in Computational Data Sets
IEEE Transactions on Visualization and Computer Graphics
Volumetric video compression for interactive playback
Computer Vision and Image Understanding - Model-based and image-based 3D scene representation for interactive visalization
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Numerical simulation of physical phenomena is now an accepted way of scientific inquiry. However, the field is still evolving, with a profusion of new solution and grid-generation techniques being continuously proposed. Concurrent and retrospective visualization are being used to validate the results, compare them among themselves and with experimental data, and browse through large scientific databases. There exists a need for representation schemes which allow access of structures in an increasing order of smoothness (or decreasing order of significance). We describe our methods on datasets obtained from curvilinear grids. Our target application required visualization of a computational simulation performed on a very remote supercomputer. Since no grid adaptation was performed, it was not deemed necessary to simplify or compress the grid. In essence, we treat the solution as if it were in the computational domain. Inherent to the identification of significant structures is determining the location of the scale coherent structures and assigning saliency values to them [22], [23]. Scale coherent structures are obtained as a result of combining the coefficients of a wavelet transform across scales. The result of this operation is a correlation mask that delineates regions containing significant structures. A spatial subdivision (e.g., octree) is used to delineate regions of interest. The mask values in these subdivided regions are used as a measure of information content. Later, another wavelet transform is conducted within each subdivided region and the coefficients are sorted based on a perceptual function with bandpass characteristics. This allows for ranking of structures based on the order of significance, giving rise to an adaptive and embedded representation scheme. We demonstrate our methods on two datasets from computational field simulations. Essentially, we show how our methods allow the ranked access of significant structures. We also compare our adaptive representation scheme with a fixed blocksize scheme.