Out-of-core compression and decompression of large n-dimensional scalar fields

We present a simple method for compressing very large and regularly sampled scalar fields. Our method is particularlyattractive when the entire data set does not fit in memory and when the sampling rate is high relative to thefeature size of the scalar field in all dimensions. Although we report res...

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Veröffentlicht in:Computer graphics forum Jg. 22; H. 3; S. 343 - 348
Hauptverfasser: Ibarria, Lawrence, Lindstrom, Peter, Rossignac, Jarek, Szymczak, Andrzej
Format: Journal Article Tagungsbericht
Sprache:Englisch
Veröffentlicht: Oxford, UK Blackwell Publishing, Inc 01.09.2003
Schlagworte:
BUFFERS
COMPRESSION
DIMENSIONS
GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
IMPLEMENTATION
POLYNOMIALS
SAMPLING
SCALAR FIELDS
ISSN:0167-7055, 1467-8659
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Beschreibung
Zusammenfassung:We present a simple method for compressing very large and regularly sampled scalar fields. Our method is particularlyattractive when the entire data set does not fit in memory and when the sampling rate is high relative to thefeature size of the scalar field in all dimensions. Although we report results for and data sets, the proposedapproach may be applied to higher dimensions. The method is based on the new Lorenzo predictor, introducedhere, which estimates the value of the scalar field at each sample from the values at processed neighbors. The predictedvalues are exact when the n‐dimensional scalar field is an implicit polynomial of degree n− 1. Surprisingly,when the residuals (differences between the actual and predicted values) are encoded using arithmetic coding,the proposed method often outperforms wavelet compression in anL∞sense. The proposed approach may beused both for lossy and lossless compression and is well suited for out‐of‐core compression and decompression,because a trivial implementation, which sweeps through the data set reading it once, requires maintaining only asmall buffer in core memory, whose size barely exceeds a single (n−1)‐dimensional slice of the data. Categories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Compression, scalar fields,out‐of‐core.
Bibliographie:ArticleID:CGF681
istex:A98337AAF9A43C51343A0D777961B5C88EA767B4
ark:/67375/WNG-L15QF6VR-L
W-7405-ENG-48
UCRL-JC-151934
US Department of Energy (US)
ISSN:0167-7055
1467-8659
DOI:10.1111/1467-8659.00681