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通过对空间相关噪声进行多尺度非局部协同滤波减少环形伪影

Ring artifact reduction via multiscale nonlocal collaborative filtering of spatially correlated noise.

作者信息

Mäkinen Ymir, Marchesini Stefano, Foi Alessandro

机构信息

Tampere University, Finland.

SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025, USA.

出版信息

J Synchrotron Radiat. 2021 May 1;28(Pt 3):876-888. doi: 10.1107/S1600577521001910. Epub 2021 Apr 16.

Abstract

X-ray micro-tomography systems often suffer severe ring artifacts in reconstructed images. These artifacts are caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw sinogram data. In this work, these streaks are modeled in the sinogram domain as additive stationary correlated noise upon logarithmic transformation. Based on this model, a streak removal procedure is proposed where the Block-Matching and 3-D (BM3D) filtering algorithm is applied across multiple scales, achieving state-of-the-art performance in both real and simulated data. Specifically, the proposed fully automatic procedure allows for attenuation of streak noise and the corresponding ring artifacts without creating major distortions common to other streak removal algorithms.

摘要

X射线显微断层扫描系统在重建图像中常常出现严重的环形伪影。这些伪影是由探测器缺陷、校准误差以及在原始正弦图数据中产生条纹噪声的波动所引起的。在这项工作中,这些条纹在正弦图域中通过对数变换被建模为加性平稳相关噪声。基于该模型,提出了一种条纹去除方法,其中在多个尺度上应用块匹配三维(BM3D)滤波算法,在真实数据和模拟数据中均实现了一流的性能。具体而言,所提出的全自动方法能够减弱条纹噪声以及相应的环形伪影,而不会产生其他条纹去除算法常见的重大失真。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fefd/8127377/4f2f527b55b2/s-28-00876-fig1.jpg

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