Computational Spectral Imaging

in Special Issue   Posted on February 12, 2021 

Information for the Special Issue

Submission Deadline: Wed 31 Mar 2021
Journal Impact Factor : 3.275
Journal Name : Sensors
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Computational spectral imaging devices acquire multi- and hyper-spectral images of a scene by leveraging image and signal processing techniques. Examples of computational imaging devices are multispectral sensors based on spectral filter arrays, hyperspectral cameras based on compressed sensing, Fourier transform spectrometers, light field cameras, and multimodal sensors. Computational systems overcome the limits of conventional imaging devices allowing, for example, to acquire images that simultaneously sample the spatial, depth, and spectral information of a scene (i.e., snapshot), achieve a higher spatial and spectral resolution, and even to access additional information of a scene (e.g., depth).
However, computational devices require typically more complex processing of the acquisitions, relying on advanced signal and image processing techniques (e.g., compressed sensing, inverse problems for image reconstruction, demosaicing, and image fusion).

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