Open Access

Development and Evaluation of High-Performance Decorrelation Algorithms for the Nonalternating 3D Wavelet Transform

EURASIP Journal on Advances in Signal Processing20072007:069384

Received: 2 September 2006

Accepted: 27 March 2007

Published: 17 May 2007


We introduce and evaluate the implementations of three parallel video-sequences decorrelation algorithms. The proposed algorithms are based on the nonalternating classic three-dimensional wavelet transform (3D-WT). The parallel implementations of the algorithms are developed and tested on a shared memory system, an SGI origin 3800 supercomputer making use of a message-passing paradigm. We evaluate and analyze the performance of the implementations in terms of the response time and speed-up factor by varying the number of processors and various video coding parameters. The key points enabling the development of highly efficient implementations rely on the partitioning of the video sequences into groups of frames and a workload distribution strategy supplemented by the use of parallel I/O primitives, for better exploiting the inherent features of the application and computing platform. We also evaluate the effectiveness of our algorithms in terms of the first-order entropy.


Authors’ Affiliations

Departamento de Tecnologías y Sistemas de Informaciòn, Universidad de Castilla-La Mancha
Departamento de Sistemas Tecnologías, Universidad de Castilla-La Mancha


  1. Feil M, Uhl A: Efficient wavelet-based video coding. Proceedings of the 16th International Parallel and Distributed Processing Symposium (IPDPS '02), April 2002, Fort Lauderdale, Fla, USA 139.Google Scholar
  2. Nielsen OL, Hegland M: Parallel performance of fast wavelet transforms. International Journal of High Speed Computing 2000,11(1):55-74. 10.1142/S0129053300000059View ArticleMATHGoogle Scholar
  3. Moyano-Ávila E, Quiles FJ, Orozco-Barbosa L: Algorithms based on the standard wavelet transform for angiography sequences decomposition. In World Congress on Medical Physics and Biomedical Engineering. Springer, New York, NY, USA; 2006.Google Scholar
  4. Fournier A: Wavelets and their applications in computer graphics. Proceedings of the 22nd Annual Conference on Computer Graphics (SIGGRAPH '95), August 1995, Los Angeles, Calif, USA course notesGoogle Scholar
  5. Pearlman WA, Kim BJ, Xiong Z: Embedded video subband coding with 3D SPIHT. In Wavelet Image and Video Compression. Kluwer Academic Publishers, Dordrecht, The Netherlands; 1998:397-432.Google Scholar
  6. Pacheco P: Parallel Programming with MPI. Morgan Kaufmann Publishers, San Fransisco, Calif, USA; 1997.MATHGoogle Scholar
  7. Thakur R: Introduction to parallel I/O and MPI-IO. In Tutorial at 11th Annual Computing Institute, July 2005, San Diego, Calif, USA. San Diego Supercomputer Center;Google Scholar
  8. Mallat SG: Multifrequency channel decompositions of images and wavelet models. IEEE Transactions on Acoustics, Speech, and Signal Processing 1989,37(12):2091-2110. 10.1109/29.45554View ArticleGoogle Scholar
  9. Antonini M, Barlaud M, Mathieu P, Daubechies I: Image coding using wavelet transform. IEEE Transactions of Image Processing 1992,1(2):205-220. 10.1109/83.136597View ArticleGoogle Scholar
  10. Modarressi M, Sarbazi-Azad H: Parallel 3-dimensional DCT computation on k-ary n-cubes. In Proceedings of the 8th International Conference on High Performance Computing in Asia Pacific Region (HPC-Asia '05), November-December 2005, Beijing, China. IEEE Computer Society; 91-97.Google Scholar
  11. Yu H, Ma K-L: A study of I/O methods for parallel visualization of large-scale data. Parallel Computing 2005,31(2):167-183. 10.1016/j.parco.2005.02.004MathSciNetView ArticleGoogle Scholar
  12. Wapperom P, Beris AN, Straka MA: A new transpose split method for three-dimensional FFTs: performance on an Origin2000 and Alphaserver cluster. Parallel Computing 2006,32(1):1-13. 10.1016/j.parco.2005.06.004MathSciNetView ArticleGoogle Scholar
  13. Thulasiraman P, Khokhar AA, Heber G, Gao GR: A fine-grain load-adaptive algorithm of the 2D discrete wavelet transform for multithreaded architectures. Journal of Parallel and Distributed Computing 2004,64(1):68-78. 10.1016/j.jpdc.2003.06.003View ArticleMATHGoogle Scholar
  14. Kutil R, Uhl A: Hardware and software aspects for 3-D wavelet decomposition on shared memory MIMD computers. Proceedings of the 4th International ACPC Conference Including Special Tracks on Parallel Numerics and Parallel Computing in Image Processing, Video Processing, and Multimedia (ACPC '99), February 1999, Salzburg, Austria, Lecture Notes in Computer Science 1557: 347-356.Google Scholar
  15. Norcen R, Uhl A: High performance JPEG 2000 and MPEG-4 VTC on SMPs using OpenMP. Parallel Computing 2005,31(10–12):1082-1098.View ArticleGoogle Scholar
  16. Katona M, Pižurica A, Teslić N, Kovačević V, Philips W: A real-time wavelet-domain video denoising implementation in FPGA. EURASIP Journal of Embedded Systems 2006, 2006: 12 pages.Google Scholar
  17. Silicon Graphics Inc : SGI Origin 3000.
  18. González RC, Woods RE: Digital Image Processing. 2nd edition. Prentice-Hall, Upper Saddle River, NJ, USA; 2002.Google Scholar


© E. Moyano-Ávila et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.