The Community for Technology Leaders
RSS Icon
Issue No.12 - Dec. (2012 vol.18)
pp: 2295-2304
Nathaniel Fout , University of California, Davis
Kwan-Liu Ma , University of California, Davis
In this work, we address the problem of lossless compression of scientific and medical floating-point volume data. We propose two prediction-based compression methods that share a common framework, which consists of a switched prediction scheme wherein the best predictor out of a preset group of linear predictors is selected. Such a scheme is able to adapt to different datasets as well as to varying statistics within the data. The first method, called APE (Adaptive Polynomial Encoder), uses a family of structured interpolating polynomials for prediction, while the second method, which we refer to as ACE (Adaptive Combined Encoder), combines predictors from previous work with the polynomial predictors to yield a more flexible, powerful encoder that is able to effectively decorrelate a wide range of data. In addition, in order to facilitate efficient visualization of compressed data, our scheme provides an option to partition floating-point values in such a way as to provide a progressive representation. We compare our two compressors to existing state-of-the-art lossless floating-point compressors for scientific data, with our data suite including both computer simulations and observational measurements. The results demonstrate that our polynomial predictor, APE, is comparable to previous approaches in terms of speed but achieves better compression rates on average. ACE, our combined predictor, while somewhat slower, is able to achieve the best compression rate on all datasets, with significantly better rates on most of the datasets.
Floating-point arithmetic, Polynomials, Entropy coding, Data visualization, Image coding, Data models, floating-point compression, Volume compression, lossless compression
Nathaniel Fout, Kwan-Liu Ma, "An Adaptive Prediction-Based Approach to Lossless Compression of Floating-Point Volume Data", IEEE Transactions on Visualization & Computer Graphics, vol.18, no. 12, pp. 2295-2304, Dec. 2012, doi:10.1109/TVCG.2012.194
[1] M. Burtscher and P. Ratanaworabhan., High throughput compression of double-precision floating-point data. In Data Compression Conf ‘07, DCC ‘07, pages 293-302, march 2007.
[2] M. Burtscher and P. Ratanaworabhan, FPC: A high-speed compressor for double-precision floating-point data IEEE Trans. on Computers, 58(1): 18-31, january 2009.
[3] L. Devroye., Non-Uniform Random Variate Generation. Springer-Verlag, 1986.
[4] X. Du and R. Moorhead., Multiresolutional visualization of evolving distributed simulations using wavelets and MPI. In Scientific Visualization Conference, 1997, page 54, 1997.
[5] V. Engelson, D. Fritzson, and P. Fritzson., Lossless compression of high-volume numerical data from simulations. In Conf on Data Compression ‘00, DCC ‘00, page 574. IEEE Computer Society, 2000.
[6] M. N. Gamito and M. S. Dias., Lossless coding of floating point data with JPEG 2000 part 10 Applications of Digital Image Processing XXVII, 5558(1): 276-287, 2004.
[7] F. Ghido., An efficient algorithm for lossless compression of IEEE float audio. In Data Compression Conf ‘04, DCC ‘04, pages 429-438, march 2004.
[8] M. Hans and R. Schafer, Lossless compression of digital audio Signal Processing Magazine. IEEE, 18(4): 21-32, july 2001.
[9] J. Hauser., SoftFloat, 2002. Version 2b,
[10] L. Ibarria, P. Lindstrom, J. Rossignac,, and A. Szymczak., Out-of-core compression and decompression of large n-dimensional scalar fields. Computer Graphics Forum, 22(3): 343-348, 2003.
[11] M. Isenburg, P. Lindstrom, and J. Snoeyink, Lossless compression of predicted floating-point geometry Computer-Aided Design, 37(8): 869-877, 2005. CAD ‘04 Special Issue: Modelling and Geometry Representations for CAD.
[12] T. Liebchen, T. Moriya, N. Harada., Y. Kamamoto, and Y. Reznik., The MPEG-4 audio lossless coding (ALS) standard - technology and applications. In 119th Convention of Audio Engineering Society, October 2005.
[13] P. Lindstrom and M. Isenburg, Fast and efficient compression of floating-point data IEEE Trans. on Visualization and Computer Graphics, 12(5): 1245-1250, sept.-oct. 2006.
[14] S. Muraki, T. Nakai, Y. Kita,, and K. Tsuda., An attempt for coloring multichannel MR imaging data. IEEE Transactions on Visualization and Computer Graphics, 7(3): 265-274, July 2001.
[15] S. Pigeon., Lossless Compression Handbook, chapter Huffman Coding. Number ISBN 0–12-620861–1 in Communications, Networking, and Multimedia. Academic Press, 2003.
[16] P. Ratanaworabhan, J. Ke, and M. Burtscher., Fast lossless compression of scientific floating-point data. In Data Compression Con ‘06, pages 133-142, march 2006.
[17] T. Robinson., SHORTEN: Simple lossless and near-lossless waveform compression. Technical Report 156, Cambridge Univ. Eng. Dept., Cam-bridge, UK, 1994.
[18] K. Sayood and K. Anderson, A differential lossless image compression scheme IEEE Trans. on Signal Processing, 40(1): 236-241, jan 1992.
[19] E. R. Schendel, Y. Jin, N. Shah., J. Chen, C. S. Chang, S.-H. Ku, S. Ethier., S. Klasky, R. Latham,R. B. Ross,, and N. F. Samatova., ISOBAR precon-ditioner for effective and high-throughput lossless data compression. In ICDE, pages 138-149, 2012.
[20] C. R. Schroeder., Adaptive coarsening: simple, effective floating-point compression. In ACMIIEEE Conference on Supercomputing, SC ‘06. ACM, 2006.
[21] T. M. Shafaat and S. B. Baden., A method of adaptive coarsening for compressing scientific datasets. In Int'l. Conf on Applied Parallel Com-puting, PARA’06, pages 774-780. Springer-Verlag, 2007.
[22] H. Tao and R. Moorhead., Lossless progressive transmission of scientific data using biorthogonal wavelet transform. In IEEE Image Processing ‘94, 3, pages 373-377, nov 1994.
[23] H. Tao and R. J. Moorhead., Progressive transmission of scientific data using biorthogonal wavelet transform. In Visualization Conf ‘94, VIS ‘94, pages 93-99. IEEE Computer Society Press, 1994.
[24] H. Tomari, M. Inaba, and K. Hiraki., Compressing floating-point number stream for numerical applications. In Int'l. Conf on Networking and Computing’10, ICNC ‘10, pages 112-119, nov. 2010.
[25] A. Trott, R. Moorhead, and J. McGinley., The application of wavelets to lossless compression and progressive transmission of floating point data in 3-d curvilinear grids. In Proc. of Data Compression Conference ‘96, DCC ‘96, page 458, mar/apr 1996.
[26] A. Trott, R. Moorhead, and J. McGinley., Wavelets applied to lossless compression and progressive transmission of floating point data in 3-d curvilinear grids. In Visualization Conf ‘96, VIS ‘96, pages 385-388. IEEE Computer Society Press, 1996.
[27] B. Usevitch., JPEG2000 compliant lossless coding of floating point data. In Data Compression Conf ‘05, DCC ‘05, pages 484-484. IEEE Computer Society, 2005.
[28] B. Usevitch, JPEG2000 compatible lossless coding of floating-point data EURASIP Journal on Image and Video Processing, 2007, 2007.
[29] B. E. Usevitch., JPEG2000 extensions for bit plane coding of floating point data. In Data Compression Conf ‘03, DCC ‘03, page 451. IEEE Computer Society, 2003.
[30] B. Wohlberg and C. Brislawn., JPEG 2000 part 10: Floating point coding. Technical Report 2644, ISO/IEC JTC l/SC29IWG 1, 2002.
[31] X. Xie and Q. Qin., Fast lossless compression of seismic floating-point data. In Int'l. Forum on Information Technology and Applications ‘09, 1 of IFITA ‘09, pages 235-238, may 2009.
[32] D. Yang, T. Moriya, and T. Liebchen., A lossless audio compression scheme with random access property. In IEEE Conf Acoustics, Speech, and Signal Processing ‘04, 3 of ICASSP ‘04, pages 1016-1019, may 2004.
[33] Y. You and M. Y. Sung., Haptic data transmission based on the prediction and compression. In IEEE Conf on Communications ‘08, ICC ‘08, pages 1824-1828, may 2008.
[34] T. Zhou, Y. Liu, Q. Chen., K. Cai, J. Teng,, and Z. Chen., An entropy coding method for floating-point texture coordinates of 3D mesh. In IEEE Int'l. Symp. on Circuits and Systems’ 10, ISCAS ‘10, pages 1835-1838, june 2010.
15 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool