摘要
现有二维非局部均值降噪算法仅能抑制三维图像的层内噪声,无法利用层间信息对图像进一步降噪。针对该问题,分析印刷电路板在锥形束CT系统中所成图像的自相似性,将现有二维算法扩展到三维空间,提出基于分块处理的三维非局部均值降噪算法。实验结果表明,该算法可进一步抑制噪声,具有较高的计算效率。
Existing 2D non-local mean noise reduction algorithm can only suppress the noise inside the slice, it can not access the noise between slices. Aiming at this problem, this paper analyzes image self-similarity which is generated by Printed Circuit Board（PCB） in Cone Beam Computed Tomography（CBCT）, extends existing 2D algorithm to 3D space, and proposes 3D non-local mean noise reduction algorithm based on partitioning processing. Experimental results show that this algorithm can further restrain noise, and it has higher computational efficiency.
出处
《计算机工程》
CAS
CSCD
北大核心
2010年第7期220-223,共4页
Computer Engineering
基金
河南省基础与前沿技术研究计划基金资助项目(072300450240)
关键词
工业CT
三维图像
图像降噪
分块
非局部均值降噪
Industry Computed Tomography（ICT）
3D image
image noise reduction
partitioning
non-local mean noise reduction
