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. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Gong, M., Langille, A., & Gong, M. (2005). Real-time image processing using graphics hardware: A performance study. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3656 LNCS, pp. 1217–1225). https://doi.org/10.1007/11559573_147
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