  Electron microscopy has shown to be a very powerful tool to map the chemical
nature of samples at various scales down to atomic resolution. However, many
samples can not be analyzed with an acceptable signal-to-noise ratio because of
the radiation damage induced by the electron beam. This is particularly crucial
for electron energy loss spectroscopy (EELS) which acquires spectral-spatial
data and requires high beam intensity. Since scanning transmission electron
microscopes (STEM) are able to acquire data cubes by scanning the electron
probe over the sample and recording a spectrum for each spatial position, it is
possible to design the scan pattern and to sample only specific pixels. As a
consequence, partial acquisition schemes are now conceivable, provided a
reconstruction of the full data cube is conducted as a post-processing step.
This paper proposes two reconstruction algorithms for multi-band images
acquired by STEM-EELS which exploits the spectral structure and the spatial
smoothness of the image. The performance of the proposed schemes is illustrated
thanks to experiments conducted on a realistic phantom dataset as well as real
EELS spectrum-images.
