Analytical Fresnel imaging models for photon sieves


ÖKTEM S. F. , Kamalabadi F., Davila J. M.

OPTICS EXPRESS, cilt.26, sa.24, ss.32259-32279, 2018 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 26 Konu: 24
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1364/oe.26.032259
  • Dergi Adı: OPTICS EXPRESS
  • Sayfa Sayıları: ss.32259-32279

Özet

Photon sieves are a fairly new class of diffractive lenses that open unprecedented possibilities for high resolution imaging and spectroscopy, especially at short wavelengths such as UV and x-rays. In this paper, we model and analyze the image formation process of photon sieves using Fourier optics. We derive closed-form Fresnel imaging models that relate an input object to the image formed by a photon sieve system, both for coherent and incoherent illumination. These analytical models also provide a closed-form expression for the point-spread function of the system for both in-focus and out-of-focus cases. All the formulas are expressed in terms of Fourier transforms and convolutions, which enable easy interpretation as well as fast computation. The derived analytical models provide a unified framework to effectively develop new imaging modalities enabled by diffractive lenses and analyze their imaging capabilities for different design configurations, prior to physical production. To illustrate their utility and versatility, the derived formulas are applied to several important special cases such as photon sieves with circular holes and pixelated diffractive lenses generated by SLM-type devices. The analytical image formation models presented in this paper provide a generalizable and powerful means for effective analysis and simulation of any imaging system with a diffractive lens, including Fresnel zone plates, Fresnel phase plates, and other modified Fresnel lenses and mask-like patterns such as coded apertures. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement