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相关论文: Phase retrieval by iterated projections

200 篇论文

We consider a variant of the phase retrieval problem, where vectors are replaced by unitary matrices, i.e., the unknown signal is a unitary matrix U, and the measurements consist of squared inner products |Tr(C*U)|^2 with unitary matrices C…

量子物理 · 物理学 2018-03-07 Shelby Kimmel , Yi-Kai Liu

Phase imaging techniques extract the optical path-length information of a scene, whereas wavefront sensors provide the shape of an optical wavefront. Since these two applications have different technical requirements, they have developed…

光学 · 物理学 2018-02-28 F. Soldevila , V. Durán , P. Clemente , J. Lancis , E. Tajahuerce

The phase retrieval from multi-frequency intensity (power) observations is considered. The object to be reconstructed is complex-valued. A novel algorithm is presented that accomplishes both the object phase (absolute phase) retrieval and…

信号处理 · 电气工程与系统科学 2018-02-07 Vladimir Katkovnik , Karen Egiazarian

Characterizing the phase space distribution of particle beams in accelerators is a central part of accelerator understanding and performance optimization. However, conventional reconstruction-based techniques either use simplifying…

We experimentally demonstrate how to solve the phase problem of diffraction using multi-wave interference with standard diffraction experimental setups without the need for taking any auxiliary data. In particular, we show that the phases…

光学 · 物理学 2021-05-04 M. Fally , Y. Tomita , A. Fimia , R. F. Madrigal , J. Guo , J. Kohlbrecher , J. Klepp

In this paper we consider the following real-valued and finite dimensional specific instance of the 1-D classical phase retrieval problem. Let ${\bf F}\in\mathbb{R}^N$ be an $N$-dimensional vector, whose discrete Fourier transform has a…

数值分析 · 数学 2016-04-26 Ben Leshem , Oren Raz , Ariel Jaffe , Boaz Nadler

Phase retrieval (PR), also sometimes referred to as quadratic sensing, is a problem that occurs in numerous signal and image acquisition domains ranging from optics, X-ray crystallography, Fourier ptychography, sub-diffraction imaging, and…

机器学习 · 计算机科学 2020-06-25 Namrata Vaswani

As a generalization of the standard phase retrieval problem, we seek to reconstruct symmetric rank-1 matrices from inner products with subclasses of positive semidefinite matrices. For such subclasses, we introduce random cubatures for…

数值分析 · 数学 2017-09-04 Martin Ehler , Manuel Graef , Franz J. Kiraly

Real-valued Phase retrieval is a non-convex continuous inference problem, where a high-dimensional signal is to be reconstructed from a dataset of signless linear measurements. Focusing on the noiseless case, we aim to disentangle the two…

无序系统与神经网络 · 物理学 2025-02-07 Davide Straziota , Luca Saglietti

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 due to its nonlinear…

图像与视频处理 · 电气工程与系统科学 2025-01-20 Cagatay Isil , Figen S. Oktem

The generalized phase retrieval problem over compact groups aims to recover a set of matrices -- representing an unknown signal -- from their associated Gram matrices. This framework generalizes the classical phase retrieval problem, which…

信号处理 · 电气工程与系统科学 2025-11-20 Tal Amir , Tamir Bendory , Nadav Dym , Dan Edidin

This paper considers the phase retrieval problem in which measurements consist of only the magnitude of several linear measurements of the unknown, e.g., spectral components of a time sequence. We develop low-complexity algorithms with…

信息论 · 计算机科学 2016-08-24 Tianyu Qiu , Prabhu Babu , Daniel P. Palomar

Edidin [3] proved a fundamental result in phase retrieval: Theorem: A family of orthogonal projections $\{P_i\}_{i=1}^m$ does phase retrieval in $\mathbb{R}^n$ if and only if for every $0\not= x\in \mathbb{R}^n$, the family…

泛函分析 · 数学 2021-03-11 Peter G. Casazza , Janet C. Tremain

Phase retrieval in dynamical sampling is a novel research direction, where an unknown signal has to be recovered from the phaseless measurements with respect to a dynamical frame, i.e. a sequence of sampling vectors constructed by the…

数值分析 · 数学 2021-03-19 Robert Beinert , Marzieh Hasannasab

In this short note we propose a simple two-stage sparse phase retrieval strategy that uses a near-optimal number of measurements, and is both computationally efficient and robust to measurement noise. In addition, the proposed strategy is…

数值分析 · 数学 2015-04-27 Mark Iwen , Aditya Viswanathan , Yang Wang

The multi-plane phase retrieval method provides a budget-friendly and effective way to perform phase imaging, yet it often encounters alignment challenges due to shifts along the optical axis in experiments. Traditional methods, such as…

光学 · 物理学 2024-05-01 Jiabao Wang , Yang Wu , Jun Wang , Ni Chen

In this work, issues in phase retrieval in the coherent diffractive imaging (CDI) technique, from discussion on parameters for setting up a CDI experiment to evaluation of the goodness of the final reconstruction, are discussed. The…

光学 · 物理学 2018-11-01 Tatiana Latychevskaia

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…

声音 · 计算机科学 2020-12-01 Pierre-Hugo Vial , Paul Magron , Thomas Oberlin , Cédric Févotte

The principal limitation in many areas of astronomy, especially for directly imaging exoplanets, arises from instability in the point spread function (PSF) delivered by the telescope and instrument. To understand the transfer function, it…

天体物理仪器与方法 · 物理学 2021-09-01 Alison Wong , Benjamin Pope , Louis Desdoigts , Peter Tuthill , Barnaby Norris , Chris Betters

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 unsupervised posterior…

图像与视频处理 · 电气工程与系统科学 2025-01-07 Mehmet Onurcan Kaya , Figen S. Oktem
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