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稀疏计算层析成像重构中迭代去噪方法的分析

Analysis of Iterative Denoising Method in Sparse Computed Tomography Reconstruction

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摘要

研究了稀疏计算层析成像重构中的迭代去噪模型及其求解算法, 理论推导及模拟实验验证了代数重构技术的抑噪能力.根据稀疏计算层析成像成像过程的噪音特征, 提出了基于欧氏范数不等式约束和基于无穷范数不等式约束的去噪模型.提出了基于凸集投影方法求解去噪模型的算法, 并给出了算法推导过程.结果表明: 欧氏范数去噪模型优于无穷范数去噪模型, 代数重构技术具有抑制噪音的作用.

Abstract

The iterative denoising models and their solving algorithms in the sparse computed tomoyraphy reconstruction were researched. The theoretical derivations and simulation experiments demonstrate that the Algebraic Reconstruction Technique (ART) have the denoising ability. Two models for the sparse computed tomoyraphy denoise were proposed. One is based on the Euclidean norm inequality constraint, and the other is based on the infinity norm inequality constraint. Inspaired by the iterative method in ART, we use projection onto convex sets method to solve these two denoising models. The algorithm derivation is provided. The results indicate that the Euclidean norm based denoise model is better than the infinity norm based denoise model, and the ART method has the ability of denoising.

Newport宣传-MKS新实验室计划
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中图分类号:R318.6

DOI:10.3788/gzxb20154405.0517002

基金项目:国家自然科学基金(No.61201037)资助

收稿日期:2014-12-22

修改稿日期:2015-02-09

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作者单位    点击查看

李宏霄:天津大学 精密仪器与光电子工程学院, 光电信息技术教育部重点实验室, 天津 300072
陈晓冬:天津大学 精密仪器与光电子工程学院, 光电信息技术教育部重点实验室, 天津 300072
李俊威:天津大学 精密仪器与光电子工程学院, 光电信息技术教育部重点实验室, 天津 300072
汪毅:天津大学 精密仪器与光电子工程学院, 光电信息技术教育部重点实验室, 天津 300072
郁道银:天津大学 精密仪器与光电子工程学院, 光电信息技术教育部重点实验室, 天津 300072

联系人作者:李宏霄(hxli@tju.edu.cn)

备注:李宏霄(1986-), 男, 博士研究生, 主要研究方向为医学图像处理.

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引用该论文

LI Hong-xiao,CHEN Xiao-dong,LI Jun-wei,WANG Yi,YU Dao-yin. Analysis of Iterative Denoising Method in Sparse Computed Tomography Reconstruction[J]. ACTA PHOTONICA SINICA, 2015, 44(5): 0517002

李宏霄,陈晓冬,李俊威,汪毅,郁道银. 稀疏计算层析成像重构中迭代去噪方法的分析[J]. 光子学报, 2015, 44(5): 0517002

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