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Related papers: Octonion Phase Retrieval

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Phase recovery (PR) refers to calculating the phase of the light field from its intensity measurements. As exemplified from quantitative phase imaging and coherent diffraction imaging to adaptive optics, PR is essential for reconstructing…

We introduce a generalized version of phase retrieval called multiplexed phase retrieval. We want to recover the phase of amplitude-only measurements from linear combinations of them. This corresponds to the case in which multiple…

Image and Video Processing · Electrical Eng. & Systems 2019-07-02 Jonathan Dong , Florent Krzakala , Sylvain Gigan

Alternative reconstruction method is proposed on retrieving the object exit wave function (OEW) directly from the recorded image intensity pattern in high resolution transmission electron microscopy (HRTEM). The method is based on applying…

Materials Science · Physics 2021-03-02 Usha Bhat , Ranjan Datta

Conventional Fourier-domain Optical Coherence Tomography (FD-OCT) systems depend on resampling into wavenumber (k) domain to extract the depth profile. This either necessitates additional hardware resources or amplifies the existing…

Optics · Physics 2025-09-24 Maryam Viqar , Erdem Sahin , Elena Stoykova , Violeta Madjarova

One of the most prominent challenges in the field of diffractive imaging is the phase retrieval (PR) problem: In order to reconstruct an object from its diffraction pattern, the inverse Fourier transform must be computed. This is only…

Image and Video Processing · Electrical Eng. & Systems 2022-05-06 Simon Welker , Tal Peer , Henry N. Chapman , Timo Gerkmann

Spectroscopy requires high-precision wavelength discrimination but typically requires bulky, alignment-sensitive instrumentation. To address this, we present a compact computational spectrometer built from a single germanium PN photodiode.…

This paper considers the problem of recovering a $k$-sparse, $N$-dimensional complex signal from Fourier magnitude measurements. It proposes a Fourier optics setup such that signal recovery up to a global phase factor is possible with very…

Information Theory · Computer Science 2014-10-28 Çağkan Yapar , Volker Pohl , Holger Boche

The classical phase retrieval refers to the recovery of an unknown signal from its Fourier magnitudes, which is widely used in fields such as quantum mechanics, signal processing, optics, etc. The offset linear canonical transform (OLCT),…

Signal Processing · Electrical Eng. & Systems 2025-06-05 Jing Liu , Haiye Huo

A novel phase retrieval algorithm for broadband hyperspectral phase imaging from noisy intensity observations is proposed. It utilizes advantages of the Fourier Transform spectroscopy in the self-referencing optical setup and provides,…

Image and Video Processing · Electrical Eng. & Systems 2020-06-03 Igor Shevkunov , Vladimir Katkovnik , Karen Egiazarian

Reconstruction of multidimensional signals from the samples of their partial derivatives is known to be a standard problem in inverse theory. Such and similar problems routinely arise in numerous areas of applied sciences, including optical…

Numerical Analysis · Computer Science 2015-05-30 Mohammad Rostami , Oleg Michailovich , Zhou Wang

Conventional optical coherent receivers capture the full electrical field, including amplitude and phase, of a signal waveform by measuring its interference against a stable continuous-wave local oscillator (LO). In optical coherent…

Signal Processing · Electrical Eng. & Systems 2020-06-24 Haoshuo Chen , Nicolas K. Fontaine , Joan M. Gene , Roland Ryf , David T. Neilson , Gregory Raybon

Phase retrieval consists in the recovery of an unknown signal from phaseless measurements of its usually complex-valued Fourier transform. Without further assumptions, this problem is notorious to be severe ill posed such that the recovery…

Information Theory · Computer Science 2023-01-19 Robert Beinert , Saghar Rezaei

Phase retrieval (PR) is a crucial problem in many imaging applications. This study focuses on resolving the holographic phase retrieval problem in situations where the measurements are affected by a combination of Poisson and Gaussian…

Signal Processing · Electrical Eng. & Systems 2023-09-22 Zongyu Li , Jason Hu , Xiaojian Xu , Liyue Shen , Jeffrey A. Fessler

If the phase retrieval problem can be solved by a method similar to that of solving a system of linear equations under the context of FFT, the time complexity of computer based phase retrieval algorithm would be reduced. Here I present such…

Numerical Analysis · Mathematics 2013-05-20 Yuan Sun

Phase retrieval consists in the recovery of a complex-valued signal from intensity-only measurements. As it pervades a broad variety of applications, many researchers have striven to develop phase-retrieval algorithms. Classical approaches…

Fourier phase retrieval is a classical problem that deals with the recovery of an image from the amplitude measurements of its Fourier coefficients. Conventional methods solve this problem via iterative (alternating) minimization by…

Image and Video Processing · Electrical Eng. & Systems 2020-07-30 Rakib Hyder , Zikui Cai , M. Salman Asif

Fourier phase retrieval (FPR) is a challenging task widely used in various applications. It involves recovering an unknown signal from its Fourier phaseless measurements. FPR with few measurements is important for reducing time and hardware…

Image and Video Processing · Electrical Eng. & Systems 2023-07-19 Liyuan Ma , Hongxia Wang , Ningyi Leng , Ziyang Yuan

Quantitative phase imaging has been extensively studied in X-ray microtomography to improve the sensitivity and specificity of measurements, especially for low atomic number materials. However, obtaining quantitative phase images typically…

Optics · Physics 2026-02-25 KyeoReh Lee , Herve Hugonnet , Jae-Hong Lim , YongKeun Park

Phase retrieval aims to recover a signal from magnitude or power spectra measurements. It is often addressed by considering a minimization problem involving a quadratic cost function. We propose a different formulation based on Bregman…

Sound · Computer Science 2020-12-01 Pierre-Hugo Vial , Paul Magron , Thomas Oberlin , Cédric Févotte

We consider the problem of reconstructing an $n$-dimensional $k$-sparse signal from a set of noiseless magnitude-only measurements. Formulating the problem as an unregularized empirical risk minimization task, we study the sample complexity…

Machine Learning · Statistics 2021-02-25 Fan Wu , Patrick Rebeschini