Sevinç Figen Öktem

E-mail

figeno@metu.edu.tr

Department

Department of Electrical and Electronics Engineering

ORCID

0000-0002-7882-5120

Scopus Author ID

35103071500

Web of Science Researcher ID

A-9569-2018

DDRM-PR: Fourier phase retrieval using denoising diffusion restoration models Kaya, Mehmet Onurcan; Öktem, Sevinç Figen (2025-02-10) Diffusion models have demonstrated their utility as learned priors for solving various inverse problems. However, most existing approaches are limited to linear inverse problems. This paper exploits the efficient and unsup...
Deep plug-and-play HIO approach for phase retrieval Işil, Çağatay; Öktem, Sevinç Figen (2025-02-10) In the phase retrieval problem, the aim is the recovery of an unknown image from intensity-only measurements such as Fourier intensity. Although there are several solution approaches, solving this problem is challenging du...
PrNet: Efficient and Robust Phase Retrieval via Stochastic Refinement Kaya, Mehmet Onurcan; Öktem, Sevinç Figen (2025-01-01) Phase retrieval is a fundamental inverse problem that arises in many scientific and engineering disciplines, where the goal is to reconstruct a signal from intensity-only measurements. In this work, we develop prNet, a nov...
Enhanced Near-Field Microwave Imaging System with Polarization Diversity Dalkilic, A.; Öktem, Sevinç Figen; Alatan, Lale (2024-03-01) In this letter, the impact of antenna polarization configuration and polarization diversity on the imaging quality of a near-field microwave imaging system is examined. Unlike previous works, this study also develops an ef...
Plug-and-Play Regularization on Magnitude with Deep Priors for 3D Near-Field MIMO Imaging Oral, Okyanus; Öktem, Sevinç Figen (2024-01-01) Near-field radar imaging systems are used in a wide range of applications such as concealed weapon detection and medical diagnosis. In this paper, we consider the problem of reconstructing the three-dimensional (3D) comple...
Efficient physics-based learned reconstruction methods for real-time 3D near-field MIMO radar imaging Manisali, Irfan; Oral, Okyanus; Öktem, Sevinç Figen (2024-01-01) Near-field multiple-input multiple-output (MIMO) radar imaging systems have recently gained significant attention. These systems generally reconstruct the three-dimensional (3D) complex-valued reflectivity distribution of ...
Deep learning-based reconstruction for near-field MIMO radar imaging Manisali, Irfan; Öktem, Sevinç Figen (2023-01-01) Near-field multiple-input multiple-output (MIMO) radar imaging systems are of interest in diverse fields such as medicine, through-wall imaging, and surveillance. The imaging performance of these systems highly depends on ...
Computational optical sensing and imaging 2021: feature issue introduction Ke, Jun; Alieva, Tatiana; Öktem, Sevinç Figen; Silveira, Paulo E.X.; Wetzstein, Gordon; Willomitzer, Florian (2022-03-28) © 2022 Optica Publishing GroupThis Feature Issue includes 2 reviews and 34 research articles that highlight recent works in the field of Computational Optical Sensing and Imaging. Many of the works were presented at the 20...
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 r...
Computational Spectral Imaging With Diffractive Lenses And Spectral Filter Arrays Gundogan, Utku; Öktem, Sevinç Figen (2021-12-22)

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