微型电脑应用2017，Vol.33Issue(10)：22-23,32,3.
基于GPU并行计算的图像去噪研究
Research on Image Denoising Based on GPU Parallel Computing
摘要
Abstract
In order to better preserve the image denoising feature information,improve the image denoising algorithm,combined with the principle of nonlocal means algorithm,an image denoising method based on GPU parallel computing is proposed.For better preservation of the denoised image information Euclidean distance and neighborhood correlation coefficient method are used to measure of similarity between fields.Secondly in order to improve the algorithm executing rate,the image is copied to the GPU memory,then the results will be copied to the host machine,thus the main overhead can be saved.Finally,the images with different noise levels are tested.The results show that the proposed algorithm has obvious advantages in image speckle reduction and computation speed.关键词
图像去噪/邻域相关系数/高斯噪声/并行计算/非局部均值Key words
Image denoising/Domain correlation coefficient/Gaussian noise/Parallel computation/Nonlocal mean分类
信息技术与安全科学引用本文复制引用
刘小豫,李红..基于GPU并行计算的图像去噪研究[J].微型电脑应用,2017,33(10):22-23,32,3.基金项目
陕西省教育厅科学研究计划项目(16JK1823) （16JK1823）
咸阳师范学院专项科研基金项目(15XSYK044) （15XSYK044）
