摘要
低剂量CT在减少对人体辐射的同时也会影响图像的质量。针对低剂量CT图像噪声较大的问题,将BM3D算法应用于CT图像的去噪过程。该算法借鉴了非局部块匹配的思想,首先通过块匹配寻找图像相似块,然后将图像相似块堆叠成三维矩阵后进行协同滤波处理,再将处理结果聚合到原图像块从而还原图像。相比传统去噪算法,BM3D算法有较大优势,视觉效果更佳、PSNR值也明显提高。
Low-dose CT not only reduces the radiation to human body,but also affects the image quality.Aiming at the problem of large noise in low-dose CT images,BM3D algorithm is applied to the denoising process of CT images in this paper.Based on the idea of non-local block matching,the algorithm firstly looks for image similarity blocks through block matching,then stacks the image similarity blocks into 3D matrix and performs collaborative filtering processing,and then aggregates the processing results into the original image blocks to restore the image.Compared with the traditional denoising algorithms,BM3D algorithm has great advantages,better visual effect and significantly higher PSNR value.
作者
王志刚
冯云超
WANG Zhi-gang;FENG Yun-chao(Hunan Normal University,Changsha 410081,Hunan)
出处
《电脑与电信》
2020年第11期56-59,79,共5页
Computer & Telecommunication
