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

HAADF-STEM Image Resolution Enhancement Using High-Quality Image Reconstruction Techniques: Case of the Fe3O4(111) Surface

“…To obtain the displacement parameter, we first apply a low-pass filtering to the series and then normalized cross-correlation between each frame and the image selected as reference. We have implemented an iterative procedure to determine the reference image that reduces the global drift in the series and provides the most accurate values for registration (Bárcena-González et al, 2017). Before reconstruction, in order to increase the pixel density, we apply a 2x upsampling using bicubic interpolation (see Fig 1.b).…”

“…In the field of strain analysis we have already studied how the precision of the strain analysis can be enhanced when SR methodologies are applied to experimental images (Bárcena-González et al, 2016). In a previous paper (Bárcena-González et al, 2017) we reviewed the main registration and restoration algorithms, analysing their performance when they are applied to the field of microscopy using simulated images, and a complete methodology of Super Resolution was presented. A current trend is based on nonrigid approximations in the registration stage, however in our study we aimed at reaching similar accuracy but addressing the most complex calculations in the reconstruction stage using rigid registration.…”

Using Your Beam Efficiently: Reducing Electron Dose in the STEM via Flyback Compensation

“…Moreover, the intrinsically redundant nature of the data allows for unbiased correction of time-varying scanning-distortion/drift while preserving time-invariant sample data (Jones & Nellist, 2013; Sang & LeBeau, 2014; Jones et al, 2015; Ophus et al, 2016). These techniques also lend themselves to extension into areas including digital super-resolution (Bárcena-González et al, 2016, 2017) and simultaneous spectrum image recording and alignment (Yankovich et al, 2016; Jones et al, 2018; Wang et al, 2018), but discussion of these areas is left for later work.…”

CDrift: An Algorithm to Correct Linear Drift From A Single High-Resolution STEM Image

“…Most of them use real-space solutions needing a defect-free zone of reference in the image such as Rečnik et al (2005), Jones & Nellist (2013), and Zuo et al (2014). Another major group focuses on the correction of drift in a series of frames from the same region, such as the works proposed by Saito et al (2009), Berkels et al (2012 b ), Binev et al (2012), Sang & LeBeau (2014), Ophus et al (2016), Bárcena-González et al (2016, 2017), or Berkels & Liebscher (2019).…”