High-resolution Multi-spectral Imaging with Diffractive Lenses and Learned Reconstruction
Figen S. Oktem, O\u{g}uzhan Fatih Kar, Can Deniz Bezek, Farzad, Kamalabadi

TL;DR
This paper introduces a novel computational multi-spectral imaging technique using diffractive lenses and deep reconstruction algorithms, achieving high spatial and spectral resolution beyond physical limitations, demonstrated in EUV astrophysical imaging.
Contribution
The work develops a new multi-spectral imaging modality combining diffractive lenses with model-based deep reconstruction, enabling diffraction-limited resolution and spectral source separation.
Findings
Achieves diffraction-limited high spatial resolution.
Successfully resolves close spectral sources.
Demonstrates effectiveness in EUV astrophysical imaging.
Abstract
Spectral imaging is a fundamental diagnostic technique with widespread application. Conventional spectral imaging approaches have intrinsic limitations on spatial and spectral resolutions due to the physical components they rely on. To overcome these physical limitations, in this paper, we develop a novel multi-spectral imaging modality that enables higher spatial and spectral resolutions. In the developed computational imaging modality, we exploit a diffractive lens, such as a photon sieve, for both dispersing and focusing the optical field, and achieve measurement diversity by changing the focusing behavior of this lens. Because the focal length of a diffractive lens is wavelength-dependent, each measurement is a superposition of differently blurred spectral components. To reconstruct the individual spectral images from these superimposed and blurred measurements, model-based fast…
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