OpenCL acceleration algorithm of image median filtering based on heterogeneous platform
Image noise reduces the signal-to-noise ratio and quality of image,and denoising is one of the important steps in image processing.In this paper,an image median filtering parallel fast denoising filtering algorithm based on Open Computing Language(OpenCL)is proposed.The architecture characteristics of OpenCL and median filtering processing flow are introduced.According to the concurrent structure characteristics of Graphics Processing Unit(GPU),the image median filtering function module is optimized in parallel,and the complexity of the algorithm is reduced.By fully activating the work-groups and work-items in the workspace to improve the efficiency of data access,optimize the configuration parameters of the kernel work-group,the parallel processing of the median filter is realized.The experimental results show that under the condition that the image quality remains unchanged,compared with the serial algorithm based on CPU,the parallel algorithm based on Open Multi-Processing(OpenMP)and the parallel algorithm based on Compute Unified Device Architecture(CUDA),the parallel algorithm of image median filtering achieves 29.74 times,17.29 times and 1.15 times acceleration ratio on the NVIDIA GPU computing platform based on OpenCL architecture,respectively.The effectiveness of the algorithm and the portability of the platform are verified,and the real-time processing requirements of the application are basically met.
median filteringsalt and pepper noisegraphics processing unit(GPU)open computing language(OpenCL)parallel algorithm
万方数据
维普
