Abstract
The motivation of compressing seismic data is to reduce enormous storage space and transmission bandwidth. In this paper, a parallel compression technique is presented for large seismic data compression based on graphics processing unit (GPU). We take advantage of combinations of GPU-based parallel processing and 3D set partitioning in hierarchical tree (3D SPIHT) to accelerate the whole compression process. Experimental results show that our method achieve fast compression for very large seismic data (2.56GB) on standard PC hardware.
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References
Said, A., Pearlman, W.: An image multiresolution representation for lossless and lossy compression. IEEE Transactions on Image Processing 5, 1010–1303 (1996)
Kim, Y., Pearlman, W.: Lossless Volumetric Medical Image Compression. In: Proceedings of SPIE, Applications of Digital Image Processing, pp. 305–312 (1999)
NVIDIA CUDA Programming Guide Version 3.0, p. 2 (2010)
Deschizeaux, Blanc: Imaging Earth’s Subsurface Using CUDA. GPU Gems, p. 478 (2007)
Shi, X., Li, C., Wang, X., Li, K.: A practical approach of curved ray prestack Kirchhoff Time Migration on GPGPU. In: I Advanced Parallel Processing Technologies 8th International Symposium, pp. 165–176 (2009)
Wang, S.Q., Zhang, J.H., Yao, Z.X.: Accelerating 3D Fourier migration on graphics processing units. SEG Expanded Abstracts, 3020–3024 (2009)
Sungdae, C., William, A.P.: Error Resilient Video Coding With Improved 3-D SPIHT and Error Concealment. In: Proceedings of the SPIE Image and Video Communications and Processing 2003, vol. 5022, pp. 125–136 (2003)
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Xie, K., Yu, H.Q., Lu, G.Y. (2013). GPU-Based Large Seismic Data Parallel Compression. In: Du, Z. (eds) Intelligence Computation and Evolutionary Computation. Advances in Intelligent Systems and Computing, vol 180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31656-2_48
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DOI: https://doi.org/10.1007/978-3-642-31656-2_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31655-5
Online ISBN: 978-3-642-31656-2
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