Evaluation of high-quality image reconstruction techniques applied to high-resolution Z-contrast imaging

被引:9
|
作者
Barcena-Gonzalez, G. [1 ]
Guerrero-Lebrero, M. P. [1 ]
Guerrero, E. [1 ]
Yanez, A. [1 ]
Fernandez-Reyes, D. [2 ]
Gonzalez, D. [2 ]
Galindo, P. L. [1 ]
机构
[1] Univ Cadiz, Dept Comp Sci & Engn, Cadiz, Spain
[2] Univ Cadiz, Dept Mat Sci & Met Engn & Inorgan Chem, Cadiz, Spain
关键词
High quality image reconstruction; Registration; restoration; Z-contrast images; SUPERRESOLUTION; ALGORITHM;
D O I
10.1016/j.ultramic.2017.07.014
中图分类号
TH742 [显微镜];
学科分类号
摘要
High-quality image reconstruction techniques allow the generation of high pixel density images from a set of low-resolution micrographs. In general, these techniques consist of two main steps, namely, accurate registration, and formulation of an appropriate forward image model via some restoration method. There exist a wide variety of algorithms to cope with both stages and depending on their practical applications, some methods can outperform others, since they can be sensitive to the assumed data model, noise, drift, etc. When dealing with images generated by Z-contrast scanning transmission electron microscopes, a current trend is based on non-rigid approximations in the registration stage. In our work we aimed at reaching similar accuracy but addressing the most complex calculations in the reconstruction stage, instead of in the registration stage (as the non-rigid approaches do), but using a much smaller number of images. We review some of the most significant methods and address their shortcomings when they are applied to the field of microscopy. Simulated images with known targets will be used to evaluate and compare the main approaches in terms of quality enhancement and computing time. In addition, a procedure to determine the reference image will be proposed to minimise the global drift on the series. The best registration and restoration strategies will be applied to experimental images in order to point up the enhanced capability of this high quality image reconstruction methodology in this field. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:283 / 291
页数:9
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