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Strain mapping accuracy improvement using super‐resolution techniques
Author(s) -
BÁRCENAGONZÁLEZ G.,
GUERREROLEBRERO M.P.,
GUERRERO E.,
FERNÁNDEZREYES D.,
GONZÁLEZ D.,
MAYORAL A.,
UTRILLA A.D.,
ULLOA J.M.,
GALINDO P.L.
Publication year - 2016
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12341
Subject(s) - resolution (logic) , computer science , image resolution , artificial intelligence , signal to noise ratio (imaging) , image processing , software , computer vision , noise (video) , field (mathematics) , optics , image (mathematics) , materials science , physics , mathematics , pure mathematics , programming language
Summary Super‐resolution (SR) software‐based techniques aim at generating a final image by combining several noisy frames with lower resolution from the same scene. A comparative study on high‐resolution high‐angle annular dark field images of InAs/GaAs QDs has been carried out in order to evaluate the performance of the SR technique. The obtained SR images present enhanced resolution and higher signal‐to‐noise (SNR) ratio and sharpness regarding the experimental images. In addition, SR is also applied in the field of strain analysis using digital image processing applications such as geometrical phase analysis and peak pairs analysis. The precision of the strain mappings can be improved when SR methodologies are applied to experimental images.