非线性图像扩散LB 模型的CUDA 算法设计与实现

doi:10.3969/j.issn.0255-8297.2014.01.014

Abstract

Abstract: To improve the performance of Lattice Boltzmann (LB) method in image denoising, this paper proposes three compute unified device architecture (CUDA) algorithms to realize streaming processes of LB in nonlinear image diffusion, which are based on texture memory, shared memory, and global memory, respectively.To test effectiveness and efficiency of the GUDA algorithms, experiments were carried out with natural and composite images. The results show that GPU acceleration is 90 times faster than CPU acceleration, and the factor is proportional to the number of GPU stream processors.

Key words: image denoising, nonlinear image diffusion, LB model, CUDA algorithm

CLC Number:

TP391

ZHOU Ming, YAN Zhuang-zhi, HUANG Bin. Design and Implementation of CUDA Algorithms Based on Nonlinear Image Diffusion LB model[J]. Journal of Applied Sciences, 2014, 32(1): 85-92.

References

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Design and Implementation of CUDA Algorithms Based on Nonlinear Image Diffusion LB model

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