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High-resolution Multi-spectral Imaging with Diffractive Lenses and Learned Reconstruction

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Document pages: 34 pages

Abstract: Spectral imaging is a fundamental diagnostic technique with widespreadapplication. Conventional spectral imaging approaches have intrinsiclimitations on spatial and spectral resolutions due to the physical componentsthey rely on. To overcome these physical limitations, in this paper, we developa novel multi-spectral imaging modality that enables higher spatial andspectral resolutions. In the developed computational imaging modality, weexploit a diffractive lens, such as a photon sieve, for both dispersing andfocusing the optical field, and achieve measurement diversity by changing thefocusing behavior of this lens. Because the focal length of a diffractive lensis wavelength-dependent, each measurement is a superposition of differentlyblurred spectral components. To reconstruct the individual spectral images fromthese superimposed and blurred measurements, model-based fast reconstructionalgorithms are developed with deep and analytical priors using alternatingminimization and unrolling. Finally, the effectiveness and performance of thedeveloped technique is illustrated for an application in astrophysical imagingunder various observation scenarios in the extreme ultraviolet (EUV) regime.The results demonstrate that the technique provides not onlydiffraction-limited high spatial resolution, as enabled by diffractive lenses,but also the capability of resolving close-by spectral sources that would nototherwise be possible with the existing techniques. This work enables highresolution multi-spectral imaging with low cost designs for a variety ofapplications and spectral regimes.

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