Abstract
Programmable graphics hardware have proven to be a powerful resource for general computing. Previous research has shown that using a GPU for local image processing operations can be much faster than using a CPU. The actual speedup obtained is influenced by many factors. In this paper, we quantify the performance gain that can be achieved by using the GPU for different image processing operations under different conditions. We also compare the strengths and weaknesses of two of the current leaders in mainstream GPUs – ATI’s Radeon and nVidia’s GeForce FX. Many interesting observations are obtained through the evaluation.
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Gong, M., Langille, A., Gong, M. (2005). Real-Time Image Processing Using Graphics Hardware: A Performance Study. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2005. Lecture Notes in Computer Science, vol 3656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559573_147
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DOI: https://doi.org/10.1007/11559573_147
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29069-8
Online ISBN: 978-3-540-31938-2
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