Model-based Inversion Methods for Compressive Spectral Imaging with Diffractive Lenses

Dogan, Didem
Öktem, Sevinç Figen
We develop novel model-based inversion methods for compressive spectral imaging with diffractive lenses. These fast image reconstruction methods, exploiting data- adaptive convolutional dictionaries and sparsifying transforms, are applicable to any computational imaging problem with convolutional models.


Numerical design and investigation of plasmonic lenses for maximum power focusing
Güler, Sadri; Sür, Cem Gürkan; Ergül, Özgür Salih (2018-04-13)
We present the design and investigation of plasmonic lenses to achieve maximum power focusing for imaging applications. As opposed to commonly used slits opened on metallic structures, the designs are based on different arrangements of holes on metallic slabs. The structures are obtained via an optimization environment based on a three-dimensional numerical solver using an efficient implementation of the multilevel fast multipole algorithm (MLFMA) and optimization modules using genetic algorithm. We demonst...
Deep Learning-Based Joint Reconstruction and System Optimization for Single-Shot Compressive Spectral Imaging
Gundogan, Utku; Öktem, Sevinç Figen (2022-01-01)
We develop a joint reconstruction and system optimization method for snapshot spectral imaging with diffractive lenses. The method learns the diffractive lens design parameters jointly with a 3D deep prior in an unrolled reconstruction. Results illustrate the significance of jointly optimizing the prior and design parameters.
Parameter estimation for instantaneous spectral imaging
Öktem, Sevinç Figen; Davila, Joseph M (2014-05-04)
Spectral imaging is a fundamental diagnostic technique in physical sciences with widespread application. Conventionally, spectral imaging techniques rely on a scanning process, which renders them unsuitable for dynamic scenes. Here we study the problem of estimating the physical parameters of interest from the measurements of a non-scanning spectral imager based on a parametric model. This inverse problem, which can be viewed as a multi-frame deblurring problem, is formulated as a maximum a posteriori (MAP)...
Anlık Spektral Görüntüleme için Tasarım Eniyileme
Ayazgök, Suleyman; Öktem, Sevinç Figen (2019-08-22)
Snapshot spectral imaging enables to reconstructspectral images from a multiplexed single-shot measurement.Since an inversion is required to form the spectral images com-putationally, quantitative characterization of their performanceis essential to optimize the design. In this paper, we analyze theoptimal design of a snapshot spectral imaging technique. Thissnapshot multi-spectral imaging technique uses a diffractive lenscalled generalized photon sieve, and vari...
Analytical Fresnel imaging models for photon sieves
Öktem, Sevinç Figen; Davila, Joseph M. (The Optical Society, 2018-11-21)
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...
Citation Formats
D. Dogan and S. F. Öktem, “Model-based Inversion Methods for Compressive Spectral Imaging with Diffractive Lenses,” 2020, Accessed: 00, 2021. [Online]. Available: