53 citations · 121 across the 9 of their papers we have counts for
10 papers
I2I-PR: Deep Iterative Refinement for Phase Retrieval using Image-to-Image Diffusion Models
Mehmet Onurcan Kaya, Figen S. Oktem
Phase retrieval aims to recover a signal from intensity-only measurements, a fundamental problem in many fields such as imaging, holography, optical computing, crystallography, and…
prNet: Data-Driven Phase Retrieval via Stochastic Refinement
Mehmet Onurcan Kaya, Figen S. Oktem
Phase retrieval is an ill-posed inverse problem in which classical and deep learning-based methods struggle to jointly achieve measurement fidelity and perceptual realism. We propo…
DDRM-PR: Fourier Phase Retrieval using Denoising Diffusion Restoration Models
Mehmet Onurcan Kaya, Figen S. Oktem
Diffusion models have demonstrated their utility as learned priors for solving various inverse problems. However, most existing approaches are limited to linear inverse problems. T…
Deep Plug-and-Play HIO Approach for Phase Retrieval
Cagatay Isil, Figen S. Oktem
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 approach…
Efficient Physics-Based Learned Reconstruction Methods for Real-Time 3D Near-Field MIMO Radar Imaging
Irfan Manisali, Okyanus Oral, Figen S. Oktem
Near-field multiple-input multiple-output (MIMO) radar imaging systems have recently gained significant attention. In this paper, we develop novel non-iterative deep learning-based…
Plug-and-Play Regularization on Magnitude with Deep Priors for 3D Near-Field MIMO Imaging
Okyanus Oral, Figen S. Oktem
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 recons…
High-resolution Multi-spectral Imaging with Diffractive Lenses and Learned Reconstruction
Figen S. Oktem, Oğuzhan Fatih Kar, Can Deniz Bezek +1
Spectral imaging is a fundamental diagnostic technique with widespread application. Conventional spectral imaging approaches have intrinsic limitations on spatial and spectral reso…
Efficient Algorithms for Convolutional Inverse Problems in Multidimensional Imaging
Didem Dogan, Figen S. Oktem
Multidimensional imaging, capturing image data in more than two dimensions, has been an emerging field with diverse applications. Due to the limitation of two-dimensional detectors…
Deep Iterative Reconstruction for Phase Retrieval
Çağatay Işıl, Figen S. Oktem, Aykut Koç
Classical phase retrieval problem is the recovery of a constrained image from the magnitude of its Fourier transform. Although there are several well-known phase retrieval algorith…
Compressive Spectral Imaging with Diffractive Lenses
Oğuzhan Fatih Kar, Figen S. Oktem
Compressive spectral imaging enables to reconstruct the entire three-dimensional (3D) spectral cube from a few multiplexed images. Here, we develop a novel compressive spectral ima…