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Accelerating Multi-scale Image Fusion Algorithms Using CUDA

Seung-Hun Yoo, Jin-Hyung Park, Chang-Sung Jeong
Dept. Electron. Eng., Korea Univ., Seoul, South Korea
International Conference of Soft Computing and Pattern Recognition, 2009. SOCPAR ’09

@inproceedings{yoo2009accelerating,

   title={Accelerating Multi-scale Image Fusion Algorithms Using CUDA},

   author={Yoo, S.H. and Park, J.H. and Jeong, C.S.},

   booktitle={Soft Computing and Pattern Recognition, 2009. SOCPAR’09. International Conference of},

   pages={278–282},

   year={2009},

   organization={IEEE}

}

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Recently, fusion speed has emerged as an important factor in the image fusion and a substantial amount of memory and computing power are required for a high-speed fusion. This paper shows approaches to accelerate multi-scale image fusion speed on GPU (graphics processing unit) using CUDA (compute unified device architecture). The GPU has evolved into a very powerful and flexible streaming processor, which provides a good computational power and memory bandwidth. We implement the multi-scale image fusion algorithms using CUDA software platform of the latest version of GPU and theirs fusion speeds are compared and evaluated with implementation in Core2 Quad processor with 2.4 GHz. The GPU version achieved a speedup of 6x-8x over the CPU version.
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