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 imaging techniques using diffractive lenses and compressive sensing
Download
index.pdf
Date
2019
Author
Kar, Oğuzhan Fatih
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
307
views
233
downloads
Cite This
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 technique to obtain super-resolution using an additional coded aperture to spatially modulate the field before dispersion. We also demonstrate the capability of the system in a compressive setting where the entire three-dimensional spectral cube is reconstructed from highly compressed measurements through sparse recovery. In all of the imaging modalities, we numerically illustrate the performance for various settings and obtain promising results. Lastly, we provide a detailed analysis on the spatio-spectral resolution and optimization of the system from both analytical and numerical aspects.
Subject Keywords
Electronic surveillance
,
Electronic surveillance Technological innovations
,
Keywords: Diffractive lens
,
photon sieve
,
spectral imaging
,
sparsity
,
compressive sensing
,
inverse problems
,
super-resolution
,
image reconstruction
URI
http://etd.lib.metu.edu.tr/upload/12623490/index.pdf
https://hdl.handle.net/11511/43636
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
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 ...
Numerical and experimental evaluation of computational spectral imaging with photon sieves
Alkanat, Tunç; Öktem, Sevinç Figen; Department of Electrical and Electronics Engineering (2016)
Spectral imaging, the simultaneous imaging and spectroscopy of a radiating scene, is an important diagnostic tool for an expanding range of applications in physics, chemistry, biology, medicine, astronomy, and remote sensing. In this thesis, a recently developed computational imaging technique that enables high-resolution spectral imaging is studied both numerically and experimentally. This technique employs a diffractive imaging element called photon sieve, and distributes the image formation taskbetween t...
Deep CNN prior based image reconstruction for multispectral imaging
Manisali, İrfan; Cam, Refik; Bezek, Can Deniz; Öktem, Sevinç Figen (IEEE; 2020-10-07)
Spektral görüntüleme, fizik, kimya, biyoloji, tıp, astronomi ve uzaktan algılama gibi farklı alanlarda yaygın olarak kullanılan temel bir tanılayıcı tekniktir. Bu bildiride, hesaplamalı görüntüleme prensibine dayanan ve kırınımlı lens içeren birçoklu spektral görüntüleme tekniğine odaklanılmakta, bunun için evrişimsel sinir ağlarından yararlanan görüntü geriçatım yöntemi geliştirilmektedir. Sistemin elde ettiği ham verilerden spektral görüntülerin geriçatılması için, ters problem düzenlileştirme içeren bir ...
Engineering advanced polymeric surfaces for smart systems in biomedicine, biology, material science and nanotecnology: A cross-disciplinary approach of Biology, Chemistry and Physics (BIOPOLYSURF)
Hasırcı, Vasıf Nejat(2008-9-30)
The enormous potential of Biology in combination with Chemistry and Physics will lead to break-through advances in material science and to an abundant wealth of exploitable developments, Chemistry and Physics offer advanced tools for synthesis, characterization, theoretical understanding and manufacture of materials and devices, while Biology offer a window into the most sophisticated collection of functional nanostructures that exist. The inspiration searched in Nature will expand not only lo the use of th...
Absorbance Estimation and Gas Emissions Detection in Hyperspectral Imagery
Başkurt, Nur Didem; Gur, Yusuf; Omruuzun, Fatih; Çetin, Yasemin (2016-05-19)
Hyperspectral imaging in gas detection applications is a leading and widely studied research topic thanks to its high spectral resolution and remote detection ability. The main problems in these applications covers the leakage detection, gas identification, and quantification. The proposed algorithm aims to reach the transmittance and absorbance features of the gas and to detect the gaseous region by using the measured radiance data from the hyperspectral infrared sensors.
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
O. F. Kar, “Computational spectral imaging techniques using diffractive lenses and compressive sensing,” Thesis (M.S.) -- Graduate School of Natural and Applied Sciences. Electrical and Electronics Engineering., Middle East Technical University, 2019.