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Numerical and experimental evaluation of computational spectral imaging with photon sieves

Alkanat, Tunç
Spectral imaging, the simultaneous imaging and spectroscopy of a radiating scene, is an important diagnostic tool for an expanding range of applications in physics, chemistry, biology, medicine, astronomy, and remote sensing. In this thesis, a recently developed computational imaging technique that enables high-resolution spectral imaging is studied both numerically and experimentally. This technique employs a diffractive imaging element called photon sieve, and distributes the image formation taskbetween the photon sieve system and a data-processing unit. In the data-processing unit, the measurements obtained with the photon sieve system are used in an inverse problem framework to reconstruct the spectral images from their superimposed and blurred measurements. Here, we first develop a fast and accurate method to compute the two-dimensional point spread function (PSF) of any diffractive imaging element. Using this method, imaging properties of photon sieves are analyzed under different design scenarios. Secondly, we construct an experimental setup for the photon sieve imaging system, and PSF measurements obtained with this setup are compared with the theoretical calculations. Lastly, the image reconstruction method used to solve the inverse problem is studied and its performance is analyzed numerically for different regularization choices and various potential observing scenarios.