Spectral Imaging

Spectral imaging is used to capture fine spectrum in the Visible, NIR, or SWIR regions of an object/scene to allow for sensing application such as material characterization and object recognition and tracking using the spectral signature as input data. We focus on hyper-spectral image reconstruction from compressive 2D measurements obtained by a snapshot spectrometer CTIS.

Key research topics include:

  • Spectral image reconstruction from CTIS measurements.
  • Spatial super-resolution of hyper-spectral images.
  • Spectral image estimation from RGB data.
  • Material characterization using spectral data.

Selected publications:

Amann, Simon; Mel, Mazen; Zanuttigh, Pietro; Haist, Tobias; Kamm, Markus; Gatto, Alexander; others,

Material Characterization using a Compact Computed Tomography Imaging Spectrometer with Super-resolution Capability Proceedings Article

In: Proceedings of the 6th International Conference on Optical Characterization of Materials, OCM 2023, pp. 139–148, 2023.


Zimmermann, Markus; Amann, Simon; Mel, Mazen; Haist, Tobias; Gatto, Alexander

Deep learning-based hyperspectral image reconstruction from emulated and real computed tomography imaging spectrometer data Journal Article

In: Optical Engineering, vol. 61, no. 5, pp. 053103–053103, 2022.


Mel, Mazen; Gatto, Alexander; Zanuttigh, Pietro

Joint Reconstruction and Super Resolution of Hyper-Spectral CTIS Images Conference

BMVC, 2022.


Simonetto, Adriano; Zanuttigh, Pietro; Parret, Vincent; Sartor, Piergiorgio; Gatto, Alexander

Semi-supervised deep learning techniques for spectrum reconstruction Proceedings Article

In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 7767–7774, IEEE 2021.