A Fuzzy Metric in GPUs: Fast and Efficient Method for the Impulsive Image Noise Removal
The implementation of image correction algorithms on the CUDA platform is a relatively new field. Although the platform is easy to program, it is not easy to optimize the applications due to the number of decisions that have to be made. This paper reports an optimization study on the use of the CUDA platform to remove impulsive noise in images using fuzzy metric and the concept of peer group. The texture memory is used to speed up the access to data. In order to get the maximum bandwidth on the GPU memory, a strategy based on storing each pixel in 4 bytes is proposed.
KeywordsNoise removal in images Parallel systems GPU CUDA
This work was funded by the Spanish Ministry of Science Innovation (Project TIN2008-06570-C04-04). María would also like to acknowledge DGEST-ITCG for the scholarship awarded through the PROMEP program (Mexico).
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