Image alignment for synchrotron radiation based X-ray nano-CT

Abstract

Synchrotron radiation-based X-ray nano-imaging is a powerful tool for non-destructively studying the internal nano-scale structure of matter. Here in this paper, we review the state-of-the-art image alignment technology in the field of nano-resolution imaging, and classify and analyze the technology according to the research stage. First, through the publications of image alignment algorithm, the development direction of future research is analyzed. Then, the most effective image alignment application in the field of nano imaging based on classic image alignment algorithms is summarized. The paper also presents the feature detection operators that are useful for nano-scale image registration selected from recent feature detection research, which has important guiding significance for the specific application and optimization of nano-imaging image registration. Finally, the state-of-the-art image registration method based on deep learning is introduced, the applicability and potential of deep learning in nano-imaging registration technology are discussed, and future research directions and challenges are prospected based on different neural network characteristics.