Computational Spectral and Ultrafast Imaging via Convex Optimization

Date

2018-01-01

Author

Öktem, Sevinç Figen
Kamalabadi, Farzad

Metadata

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URI

https://www.springer.com/gp/book/9783319616087
https://hdl.handle.net/11511/86127

Relation

Handbook of Convex Optimization Methods in Imaging Science

Collections

Department of Electrical and Electronics Engineering, Book / Book chapter

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Computational Spectral Imaging with Photon Sieves Öktem, Sevinç Figen; Davila, Joseph M. (2016-01-01) Spectral imaging, the sensing of spatial information as a function of wavelength, is a widely used diagnostic technique in diverse fields such as physics, chemistry, biology, medicine, astronomy, and remote sensing. In this paper, we present a novel computational imaging modality that enables high-resolution spectral imaging by distributing the imaging task between a photon sieve system and a computer. The photon sieve system, coupled with a moving detector, provides measurements from multiple planes. Then ...
Computational spectral imaging techniques using diffractive lenses and compressive sensing Kar, Oğuzhan Fatih; Öktem, Sevinç Figen; Department of Electrical and Electronics Engineering (2019) Spectral imaging is a fundamental diagnostic technique in physical sciences with application in diverse fields such as physics, chemistry, biology, medicine, astronomy, and remote sensing. In this thesis, we first present a modified version of a high-resolution computational spectral imaging modality and develop a fast sparse recovery method to solve the associated large-scale inverse problems. This technique uses a diffractive lens called photon sieve for dispersing the optical field. We then extend this t...
Computational Spectral Imaging Techniques for High-Resolution and Instantaneous Observations of the Solar Corona Öktem, Sevinç Figen; Davila, Joseph M (2014-08-18) Spectral imaging is a fundamental diagnostic technique for the study of the solar coronal plasma, and spectral data is routinely used to measure the temperature, density, and flow velocity in coronal features. However, obtaining the spectra of a multi-dimensional region with inherently two-dimensional detectors poses intrinsic limitations on the spatio-temporal extent of the technique. In particular, slit spectrographs suffer from a limited instantaneous field-of-view (IFOV), and filter-based spectral image...
Computational Imaging and Inverse Problems: Making the Invisible Visible Öktem, Sevinç Figen (2019-09-06) Computational imaging is a rapidly evolving interdisciplinary field awarded of many Nobel prizes. In computationalopticalimaging, digitalprocessing is employed in conjunction with an optical system toformimages. That is, images are computationally formed fromsome indirectmeasurements bysolving an inverse problem. Driven by advances insignal processing techniques and faster computing platforms, this approach continuously yields the development of next-generationimaging systems in consumerelectronics, defense...

Citation Formats

S. F. Öktem and F. Kamalabadi, Computational Spectral and Ultrafast Imaging via Convex Optimization. 2018.