基于色差的并行高斯滤波算法

Y. Ma, K. Xie, Minfang Peng
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引用次数: 6

摘要

为了在图像处理中有效地去除噪声,减少原始信息的丢失,本文提出了一种基于图形处理器(GPU)的并行高斯滤波算法。该方法在进行高斯递归滤波之前,先比较像素周边和像素中心的色差,提高了GPU的计算速度。在我们的实验中,我们选择LiNa的图像(大小为512 pixel×512像素)来测试我们的算法。结果表明,该算法提高了图像的PSNR, GPU的处理速度比CPU的处理速度快8倍以上。
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A Parallel Gaussian Filtering Algorithm Based on Color Difference
In order to remove noise effectively and reduce the loss of original information in image processing, a new parallel Gaussian filtering algorithm (PGF) based on Graphics Processing Units (GPU) is presented in this letter. The proposed method compares color difference between neighboring of the pixel and the center of the pixel before making Recursive Gaussian filter, moreover it can improve the speed of calculation using GPU. In our experiment, the image of LiNa (size of 512 pixel×512 pixel) is chosen to test our algorithm. The results show that our algorithm improves the PSNR of image, and the speed of GPU processing is more than eight times faster than CPU processing.
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