16th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2008) Exploiting Data- and Thread-Level Parallelism for Image Correlation February 13-February 15 ISBN: 978-0-7695-3089-5
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/PDP.2008.75
The correlation between two signals (cross correlation) is a standard approach to feature detection. The normalized form of cross correlation (normalized correlation coefficient) is particularly used for template matching. In this case, the two-dimensional correlation of images is considered. One of its biggest drawbacks is the need for a lot of computational power, especially when many correlation coefficients are computed. This paper presents a new method for a high performance thread- and data-parallel computation of normalized cross correlation in the spatial domain. It will be shown that a speedup of up to 5 can be achieved solely by a sophisticated programming of the SIMD unit of a standard microprocessor. Furthermore, the new data-parallel implementation in the spatial domain can even outperform an (also data-parallel) frequency domain implementation.
Citation:
J? Kadidlo, Alfred Strey, "Exploiting Data- and Thread-Level Parallelism for Image Correlation," pdp, pp.407-413, 16th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2008), 2008 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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