Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Computational Spectral and Ultrafast Imaging via Convex Optimization
Date
2018-01-01
Author
Öktem, Sevinç Figen
Kamalabadi, Farzad
Metadata
Show full item record
Item Usage Stats
301
views
0
downloads
Cite This
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
Suggestions
OpenMETU
Core
Computational Spectral Imaging With Diffractive Lenses And Spectral Filter Arrays
Gundogan, Utku; Öktem, Sevinç Figen (2021-12-22)
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
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
S. F. Öktem and F. Kamalabadi,
Computational Spectral and Ultrafast Imaging via Convex Optimization
. 2018.