Open AccessSuperior techniques for eliminating ring artifacts in X-ray micro-tomography
Author(s) -
Nghia T. Vo,
Robert C. Atwood,
Michael Drakopoulos
Publication year - 2018
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.26.028396
Subject(s) - computer science , python (programming language) , tomography , computer vision , artificial intelligence , phase retrieval , optics , image quality , image processing , computer graphics (images) , algorithm , physics , image (mathematics) , fourier transform , quantum mechanics , operating system
Synchrotron-based X-ray micro-tomography systems often suffer severe ring artifacts in reconstructed images. In sinograms the artifacts appear as straight lines or stripe artifacts. These artifacts are caused by the irregular response of a detecting system giving rise to a variety of observed types of stripes: full stripes, partial stripes, fluctuating stripes, and unresponsive stripes. The use of pre-processing techniques such as distortion correction or phase retrieval blurs and enlarges these stripes. It is impossible for a single approach to remove all types of stripe artifacts. Here, we propose three techniques for tackling all of them. The proposed techniques are easy to implement; do not generate extra stripe artifacts and void-center artifacts; and give superior quality on challenging data sets and in comparison with other techniques. Implementations in Python and a challenging data set are available for download.