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 |
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| Sprache: | Englisch |
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Blackwell Publishing, Inc
01.09.2003
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| ISSN: | 0167-7055, 1467-8659 |
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| Abstract | 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. |
|---|---|
| AbstractList | 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 an
L
∞
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. 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. We present a simple method for compressing very large and regularly sampled scalar fields. Our method is particularly attractive when the entire data set does not fit in memory and when the sampling rate is high relative to the feature size of the scalar field in all dimensions. Although we report results for R{sup 3} and R{sup 4} data sets, the proposed approach may be applied to higher dimensions. The method is based on the new Lorenzo predictor, introduced here, which estimates the value of the scalar field at each sample from the values at processed neighbors. The predicted values 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 an L{infinity} sense. The proposed approach may be used 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 a small buffer in core memory, whose size barely exceeds a single n-1 dimensional slice of the data. |
| Author | Rossignac, Jarek Ibarria, Lawrence Lindstrom, Peter Szymczak, Andrzej |
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| References | E. Lum, K.-L. Ma and J. Clyne, "Texture hardware assisted rendering of time-varying volume data,"Visualization '01, pp. 262-270, 2001. C. Bajaj, I. Ihm and S. Park, "3D RGB Image Compression for Interactive Applications," ACM Transactions on Graphics, 20(1), pp. 10-38, 2001. M. Isenburg and S. Gumhold, "Out-of-Core Compression for Gigantic Polygon Meshes," ACM SIGGRAPH 2003, to appear. T. Bell, I.H. Witten and J.G. Cleary, "Modelling for Text Compression,"ACM Computing Surveys, 21(4), pp. 557-591, Dec. 1989. S. Guthe and W. Straβer, "Real-time decompression and visualization of animated volume data," Visualization '01, pp. 349-356, 2001. S. Mennon and M. Rizk, "Large-eddy simulations of three dimensional impinging jets,"Intl. J. Comp. Fluid Dynam. 7(3), pp. 275-290, 1996. A. Said and W.A. Pearlman, "A New Fast and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees,"IEEE Transactions on Circuits and Systems for Video Technology, 6(3), pp. 243-250, June 1996. J. Fowler and R. Yagel, "Lossless Compression of Volume Data," 1994 Symposium on Volume Visualization, pp. 43-50, Oct. 1994. T. Chiueh, C. Yang, T. He, H. Pfister and A. Kaufman, "Integrated volume compression and visualization," Visualization '97, pp. 329-336, Oct. 1997. J. Ho, K. Lee and D. Kriegman, "Compressing large polygonal models,"Visualization '01, pp. 133-140, 2001. C.T. Silva, Y.-J. Chiang, J. El-Sana and P. Lindstrom, "Out-Of-Core Algorithms for Scientific Visualization and Computer Graphics," Visualization '02Course Notes, Oct. 2002. C. Touma and C. Gotsman, "Triangle mesh compression,"Graphics Interface '98, pp. 26-34, 1998. V. Pascucci and R.J. Frank, "Global Static Indexing for Real-Time Exploration of Very Large Regular Grids,"Supercomputing 2001, Nov. 2001. K. Anagnostou, T. Atherton and A. Waterfall, "4D volume rendering with the Shear Warp factorisation,"Symp. Volume Visualization and Graphics '00, pp. 129-137, Oct. 2000. A. Mirin, R. Cohen, B. Curtis, W. Dannevik, A. Dimitis, M. Duchaineau, D. Eliason, D. Schikore, S. Anderson, D. Porter, P. Woodward, L. Shieh and S. White, "Very High Resolution Simulation of Compressible Turbulence on the IBM-SP System,"Supercomputing '99, 1999. Dec. 1989; 21 Oct. 1997 2001 June 1996; 6 Oct. 1994 Oct. 2002 Oct. 2000 1998 1997 Nov. 2001 June 1998 2001; 20 1996; 7 1999 e_1_2_10_9_2 e_1_2_10_11_2 e_1_2_10_8_2 e_1_2_10_12_2 e_1_2_10_10_2 Ho J. (e_1_2_10_18_2) 2001 Anagnostou K. (e_1_2_10_3_2) 2000 Lum E. (e_1_2_10_4_2) 2001 Touma C. (e_1_2_10_6_2) 1998 Chiueh T. (e_1_2_10_17_2) 1997 Pascucci V. (e_1_2_10_7_2) 2001 Silva C.T. (e_1_2_10_15_2) 2002 e_1_2_10_19_2 Fowler J. (e_1_2_10_13_2) 1994 Isenburg M. (e_1_2_10_16_2) e_1_2_10_2_2 e_1_2_10_5_2 e_1_2_10_14_2 |
| References_xml | – reference: S. Guthe and W. Straβer, "Real-time decompression and visualization of animated volume data," Visualization '01, pp. 349-356, 2001. – reference: A. Mirin, R. Cohen, B. Curtis, W. Dannevik, A. Dimitis, M. Duchaineau, D. Eliason, D. Schikore, S. Anderson, D. Porter, P. Woodward, L. Shieh and S. White, "Very High Resolution Simulation of Compressible Turbulence on the IBM-SP System,"Supercomputing '99, 1999. – reference: T. Bell, I.H. Witten and J.G. Cleary, "Modelling for Text Compression,"ACM Computing Surveys, 21(4), pp. 557-591, Dec. 1989. – reference: M. Isenburg and S. Gumhold, "Out-of-Core Compression for Gigantic Polygon Meshes," ACM SIGGRAPH 2003, to appear. – reference: J. Ho, K. Lee and D. Kriegman, "Compressing large polygonal models,"Visualization '01, pp. 133-140, 2001. – reference: E. Lum, K.-L. Ma and J. Clyne, "Texture hardware assisted rendering of time-varying volume data,"Visualization '01, pp. 262-270, 2001. – reference: V. Pascucci and R.J. Frank, "Global Static Indexing for Real-Time Exploration of Very Large Regular Grids,"Supercomputing 2001, Nov. 2001. – reference: K. Anagnostou, T. Atherton and A. Waterfall, "4D volume rendering with the Shear Warp factorisation,"Symp. Volume Visualization and Graphics '00, pp. 129-137, Oct. 2000. – reference: C. Touma and C. Gotsman, "Triangle mesh compression,"Graphics Interface '98, pp. 26-34, 1998. – reference: A. Said and W.A. Pearlman, "A New Fast and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees,"IEEE Transactions on Circuits and Systems for Video Technology, 6(3), pp. 243-250, June 1996. – reference: J. Fowler and R. Yagel, "Lossless Compression of Volume Data," 1994 Symposium on Volume Visualization, pp. 43-50, Oct. 1994. – reference: S. Mennon and M. Rizk, "Large-eddy simulations of three dimensional impinging jets,"Intl. J. Comp. Fluid Dynam. 7(3), pp. 275-290, 1996. – reference: C. Bajaj, I. Ihm and S. Park, "3D RGB Image Compression for Interactive Applications," ACM Transactions on Graphics, 20(1), pp. 10-38, 2001. – reference: C.T. Silva, Y.-J. Chiang, J. El-Sana and P. Lindstrom, "Out-Of-Core Algorithms for Scientific Visualization and Computer Graphics," Visualization '02Course Notes, Oct. 2002. – reference: T. Chiueh, C. Yang, T. He, H. Pfister and A. Kaufman, "Integrated volume compression and visualization," Visualization '97, pp. 329-336, Oct. 1997. – article-title: “Out‐of‐Core Compression for Gigantic Polygon Meshes,” publication-title: ACM SIGGRAPH 2003 – volume: 7 start-page: 275 issue: 3 year: 1996 end-page: 290 article-title: “Large‐eddy simulations of three dimensional impinging jets,” publication-title: Intl. J. Comp. Fluid Dynam. – start-page: 349 year: 2001 end-page: 356 article-title: “Real‐time decompression and visualization of animated volume data,” publication-title: Visualization '01 – start-page: 133 year: 2001 end-page: 140 article-title: “Compressing large polygonal models,” publication-title: Visualization '01 – start-page: 129 year: Oct. 2000 end-page: 137 article-title: “4D volume rendering with the Shear Warp factorisation,” publication-title: Symp. Volume Visualization and Graphics '00 – volume: 20 start-page: 10 issue: 1 year: 2001 end-page: 38 article-title: “3D RGB Image Compression for Interactive Applications,” publication-title: ACM Transactions on Graphics – start-page: 262 year: 2001 end-page: 270 article-title: “Texture hardware assisted rendering of time‐varying volume data,” publication-title: Visualization '01 – year: 1997 – year: June 1998 – year: 1999 article-title: “Very High Resolution Simulation of Compressible Turbulence on the IBM‐SP System,” publication-title: Supercomputing '99 – start-page: 329 year: Oct. 1997 end-page: 336 article-title: “Integrated volume compression and visualization,” publication-title: Visualization '97 – volume: 6 start-page: 243 issue: 3 year: June 1996 end-page: 250 article-title: “A New Fast and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees,” publication-title: IEEE Transactions on Circuits and Systems for Video Technology – start-page: 26 year: 1998 end-page: 34 article-title: “Triangle mesh compression,” publication-title: Graphics Interface '98 – start-page: 43 year: Oct. 1994 end-page: 50 article-title: “Lossless Compression of Volume Data,” publication-title: 1994 Symposium on Volume Visualization – year: Oct. 2002 article-title: “Out‐Of‐Core Algorithms for Scientific Visualization and Computer Graphics,” publication-title: Visualization '02 – year: Nov. 2001 article-title: “Global Static Indexing for Real‐Time Exploration of Very Large Regular Grids,” publication-title: Supercomputing 2001 – volume: 21 start-page: 557 issue: 4 year: Dec. 1989 end-page: 591 article-title: “Modelling for Text Compression,” publication-title: ACM Computing Surveys – ident: e_1_2_10_5_2 doi: 10.1007/978-1-4757-2939-9 – ident: e_1_2_10_19_2 – ident: e_1_2_10_16_2 article-title: “Out‐of‐Core Compression for Gigantic Polygon Meshes,” publication-title: ACM SIGGRAPH 2003 – ident: e_1_2_10_12_2 doi: 10.1145/383745.383747 – ident: e_1_2_10_9_2 doi: 10.1145/331532.331601 – year: 2001 ident: e_1_2_10_7_2 article-title: “Global Static Indexing for Real‐Time Exploration of Very Large Regular Grids,” publication-title: Supercomputing 2001 – ident: e_1_2_10_8_2 doi: 10.1145/76894.76896 – year: 2002 ident: e_1_2_10_15_2 article-title: “Out‐Of‐Core Algorithms for Scientific Visualization and Computer Graphics,” publication-title: Visualization '02 – start-page: 133 year: 2001 ident: e_1_2_10_18_2 article-title: “Compressing large polygonal models,” publication-title: Visualization '01 – start-page: 26 year: 1998 ident: e_1_2_10_6_2 article-title: “Triangle mesh compression,” publication-title: Graphics Interface '98 – start-page: 329 year: 1997 ident: e_1_2_10_17_2 article-title: “Integrated volume compression and visualization,” publication-title: Visualization '97 – ident: e_1_2_10_14_2 – start-page: 262 year: 2001 ident: e_1_2_10_4_2 article-title: “Texture hardware assisted rendering of time‐varying volume data,” publication-title: Visualization '01 – ident: e_1_2_10_11_2 doi: 10.1109/VISUAL.2001.964531 – ident: e_1_2_10_10_2 doi: 10.1109/76.499834 – ident: e_1_2_10_2_2 doi: 10.1080/10618569608940766 – start-page: 43 year: 1994 ident: e_1_2_10_13_2 article-title: “Lossless Compression of Volume Data,” publication-title: 1994 Symposium on Volume Visualization doi: 10.1145/197938.197961 – start-page: 129 year: 2000 ident: e_1_2_10_3_2 article-title: “4D volume rendering with the Shear Warp factorisation,” publication-title: Symp. Volume Visualization and Graphics '00 |
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| SubjectTerms | BUFFERS COMPRESSION DIMENSIONS GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE IMPLEMENTATION POLYNOMIALS SAMPLING SCALAR FIELDS |
| Title | Out-of-core compression and decompression of large n-dimensional scalar fields |
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