Bartuschat D, Stürmer M, Köstler H (2010)
Publication Type: Conference contribution
Publication year: 2010
Publisher: Springer-verlag
Edited Volumes: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Series: Lecture Notes in Computer Science
City/Town: Berlin Heidelberg
Book Volume: 5057
Pages Range: 557-566
Conference Proceedings Title: Parallel Processing and Applied Mathematics
Event location: Wroclaw
ISBN: 978-3-642-14389-2
URI: http://www.springerlink.com/content/JXJ06Q00R1U03516
DOI: 10.1007/978-3-642-14390-8_58
Patch-based approaches in imaging require heavy computations on many small sub-blocks of images but are easily parallelizable since usually different sub-blocks can be treated independently. In order to make these approaches useful in practical applications efficient algorithms and implementations are required. Newer architectures like the Cell Broadband Engine Architecture (CBEA) make it even possible to come close to real-time performance for moderate image sizes. In this article we present performance results for image denoising on the CBEA. The image denoising is done by finding sparse representations of signals from a given overcomplete dictionary and assuming that noise cannot be represented sparsely. We compare our results with a standard multicore implementation and show the gain of the CBEA. © 2010 Springer-Verlag Berlin Heidelberg.
APA:
Bartuschat, D., Stürmer, M., & Köstler, H. (2010). An Orthogonal Matching Pursuit Algorithm for Image Denoising on the Cell Broadband Engine. In Parallel Processing and Applied Mathematics (pp. 557-566). Wroclaw: Berlin Heidelberg: Springer-verlag.
MLA:
Bartuschat, Dominik, Markus Stürmer, and Harald Köstler. "An Orthogonal Matching Pursuit Algorithm for Image Denoising on the Cell Broadband Engine." Proceedings of the 8th International Conference, PPAM 2009, Wroclaw Berlin Heidelberg: Springer-verlag, 2010. 557-566.
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