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
High-resolution multi-spectral imaging with diffractive lenses and learned reconstruction
Date
2021-01-01
Author
Kar, Oguzhan Fatih
Öktem, Sevinç Figen
Kamalabadi, Farzad
Bezek, Can Deniz
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
218
views
0
downloads
Cite This
Spectral imaging is a fundamental diagnostic technique with widespread application. Conventional spectral imaging approaches have intrinsic limitations on spatial and spectral resolutions due to the physical components they rely on. To overcome these physical limitations, in this paper, we develop a novel multi-spectral imaging modality that enables higher spatial and spectral resolutions. In the developed computational imaging modality, we exploit a diffractive lens, such as a photon sieve, for both dispersing and focusing the optical field, and achieve measurement diversity by changing the focusing behavior of this lens. Because the focal length of a diffractive lens is wavelength-dependent, each measurement is a superposition of differently blurred spectral components. To reconstruct the individual spectral images from these superimposed and blurred measurements, model-based fast reconstruction algorithms are developed with deep and analytical priors using alternating minimization and unrolling. Finally, the effectiveness and performance of the developed technique is illustrated for an application in astrophysical imaging under various observation scenarios in the extreme ultraviolet (EUV) regime. The results demonstrate that the technique provides not only diffraction-limited high spatial resolution, as enabled by diffractive lenses, but also the capability of resolving close-by spectral sources that would not otherwise be possible with the existing techniques. This work enables high resolution multi-spectral imaging with low cost designs for a variety of applications and spectral regimes.
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85104622706&origin=inward
https://hdl.handle.net/11511/90922
Journal
IEEE Transactions on Computational Imaging
DOI
https://doi.org/10.1109/tci.2021.3075349
Collections
Department of Electrical and Electronics Engineering, Article
Suggestions
OpenMETU
Core
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)...
A Parametric Estimation Approach to Instantaneous Spectral Imaging
Öktem, Sevinç Figen; Davila, Joseph M (2014-12-01)
Spectral imaging, the simultaneous imaging and spectroscopy of a radiating scene, is a fundamental diagnostic technique in the physical sciences with widespread application. Due to the intrinsic limitation of two-dimensional (2D) detectors in capturing inherently three-dimensional (3D) data, spectral imaging techniques conventionally rely on a spatial or spectral scanning process, which renders them unsuitable for dynamic scenes. In this paper, we present a nonscanning (instantaneous) spectral imaging techn...
STATISTICAL MODELING OF THE GEOMETRIC ERROR IN CARDIAC ELECTRICAL IMAGING
Aydin, Umit; Serinağaoğlu Doğrusöz, Yeşim (2009-07-01)
Kalman filter approach provides a natural way to include the spatio-temporal prior information in cardiac electrical imaging. This study focuses on the performance of Kalman filter approach with geometric errors present in inverse Electrocardiography (ECG) problem. The geometric errors considered here are the wrong determination of the heart's size and location. In addition to Kalman filtering, we also compare the performances of Tikhonov regularization and Bayesian MAP estimation when geometric errors are ...
Cramer Rao bounds and instrument optimization for slitless spectroscopy
Öktem, Sevinç Figen; Davila, Joseph (2013-05-26)
Spectroscopy is a fundamental diagnostic technique in physical sciences with widespread application. Multi-order slitless imaging spectroscopy has been recently proposed to overcome the limitations of traditional spectrographs, in particular their small instantaneous field of view. Since an inversion is required to infer the physical parameters of interest from slitless spectroscopic measurements, a rigorous theory is essential for quantitative characterization of their performance. In this paper we develop...
Enhancing induced current magnetic resonance electrical impedance tomography ICMREIT image reconstruction
NAJI, NASHWAN; EROĞLU, HASAN HÜSEYİN; SÜMSER, KEMAL; SADIGHI, MEHDI; Eyüboğlu, Behçet Murat (2016-02-15)
Induced Current Magnetic Resonance Electrical Impedance Tomography (ICMREIT) is an emerging imaging methodology that utilizes Magnetic Resonance Imaging (MRI) techniques to visualize the electrical conductivity as a new contrast. In ICMREIT, by fast switching of gradient fields of Magnetic Resonance (MR) system eddy currents are induced in the imaging volume. The secondary magnetic field generated by the induced eddy currents can be extracted from the MR phase images. Image reconstruction algorithms then us...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
O. F. Kar, S. F. Öktem, F. Kamalabadi, and C. D. Bezek, “High-resolution multi-spectral imaging with diffractive lenses and learned reconstruction,”
IEEE Transactions on Computational Imaging
, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85104622706&origin=inward.