Abstract
In this paper we examine the performance advantages of using a GPU to execute the space variant Gaussian filtering. Our results show that the straightforward convolution GPU implementation obtains up to 8 times better performance than the best recursive algorithm (the Deriche’s filter) executed on a CPU, for useful maximum σ values. GPUs have turned out a useful option to obtain high execution performance, specially due to the emergence of high level languages for graphics hardware.
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References
Fernando, R., Kilgard, M.: The Cg Tutorial: The Definitive Guide to Programmable Realtime Graphics. Addison-Wesley, London, UK (2003)
Kessenich, J., Baldwin, D., Rost, R.: The OpenGL® Shading Language, Available HTTP: http://oss.sgi.com/projects/ogl-sample/registry/ARB/GLSLangSpec.Full.1.10.59.pdf,2004
Tan, S., Dale, J.L., Johnston, A.: Performance of three recursive algorithms for fast space-variant Gaussian filtering. Real-Time Imaging 9(3), 215–228 (2003)
Buck, I., et al.: Brook for GPUs: Stream Computing on Graphics Hardware. ACM Transactions on Graphics (August 2004)
Gerber, R.: Software Optimization Cookbook: High-Performance Recipes for the Intel® Architecture Intel Press 2005.
Buck, I., Purcell, T.: A Toolkit for Computation on GPUs. In: Fernado, R. (ed.) GPU Gems. Programming Techniques, Tips, and Tricks for Real-Time Graphics, pp. 621–636. Addison-Wesley, Boston (2004)
Fernando, R., Kilgard, M.J.: The Cg Tutorial. The Definitive Guide to Programmable Real-Time Graphics. Addison-Wesley Press, London, UK (2003)
Mark, W., Glanville, S., Akeley, K.: Cg: A system for programming graphics hardware in a C-like language. ACM Transactions on Graphics (August 2003)
St-Laurent, S.: The COMPLETE Effect and HLSL Guide Paradoxal Press (2005)
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Dudek, R., Cuenca, C., Quintana, F. (2007). Accelerating Space Variant Gaussian Filtering on Graphics Processing Unit. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2007. EUROCAST 2007. Lecture Notes in Computer Science, vol 4739. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75867-9_123
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DOI: https://doi.org/10.1007/978-3-540-75867-9_123
Publisher Name: Springer, Berlin, Heidelberg
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