Variational Image Processing for Electron Microscopy
This talk introduces several recent methods from variational image processing tailored to data from electron microscopy. In particular, specialized methods for variants of three fundamental image processing problems will be discussed: image denoising (recovering images from noisy observations), image segmentation (decomposing an image into disjoint, "homogeneous" regions) and image registration (transforming two or more images into a common coordinate system).
First, we demonstrate that non-rigid registration techniques can be used to achieve sub-picometre precision measurements of atom positions from a series of scanning transmission electron microscopy (STEM) images at atomic scale, clearly outperforming rigid registration approaches. Then, we show how non-local denoising methods like the Block-matching and 3D filtering algorithm (BM3D) can be extended to exploit the periodicity of crystalline structures visible in atomic scale images.
This needs knowledge about the underlying crystal lattice, for which we introduce a real space method for unsupervised primitive unit cell extraction.
Moreover, to cover cases of micrographs that show materials with discontinues in the periodicity (like in case of multiple grains), we developed a novel method for multi-phase segmentation of images based on high-dimensional local feature vectors.
The denoising and segmentation techniques can be generalized to hyperspectral data, like EELS or EDX. This is still ongoing work, but the possibilities will be exemplified with preliminary results on real hyperspectral data.
Finally, we propose a novel method that jointly estimates the direction dependent STEM distortions in each image of a STEM image series at atomic scale and reconstructs the underlying atomic grid of the material by fitting the atoms with bump functions.
Prof. B. Berkels
Aachen Institute for Advanced Study in Computational Engineering Science (AICES)
RWTH Aachen University
Schinkelstr. 2
52062 Aachen
Germany
| Phone | +49 241 8099123 |
| Fax | +49 241 80628498 |
| Prof. B. Berkels | |
| Http | Prof. B. Berkels |
| AICES |