Results 31 to 40 of about 7,807,536 (173)
Norm Retrieval and Phase Retrieval by Projections [PDF]
Axioms, 2017 We make a detailed study of norm retrieval. We give several classification theorems for norm retrieval and give a large number of examples to go with the theory. One consequence is a new result about Parseval frames: If a Parseval frame is divided into two subsets with spans W 1 , W 2 and W 1 ∩ W 2 = { 0 } , then W 1 ⊥ W
Peter Casazza +3 more
openaire +4 more sources
Low-dose phase retrieval of biological specimens using cryo-electron ptychography
Nature Communications, 2020 Cryo-electron microscopy is an essential tool for high-resolution structural studies of biological systems. This method relies on the use of phase contrast imaging at high defocus to improve information transfer at low spatial frequencies at the expense ...
Liqi Zhou +16 more
semanticscholar +1 more source
Iterative phase retrieval for digital holography: tutorial. [PDF]
Journal of The Optical Society of America A-optics Image Science and Vision, 2019 This paper provides a tutorial of iterative phase retrieval algorithms based on the Gerchberg-Saxton (GS) algorithm applied in digital holography. In addition, a novel GS-based algorithm that allows reconstruction of 3D samples is demonstrated.
T. Latychevskaia
semanticscholar +1 more source
UPR: A Model-Driven Architecture for Deep Phase Retrieval [PDF]
Asilomar Conference on Signals, Systems and Computers, 2020 The problem of phase retrieval has been intriguing researchers for decades due to its appearance in a wide range of applications. The task of a phase retrieval algorithm is typically to recover a signal from linear phase-less measurements. In this paper,
Naveed Naimipour +2 more
semanticscholar +1 more source
Proximity operators for phase retrieval [PDF]
Applied Optics, 2016 We present a new formulation of a family of proximity operators that generalize the projector step for phase retrieval. These proximity operators for noisy intensity measurements can replace the classical "noise free" projection in any projection-based algorithm. They are derived from a maximum likelihood formulation and admit closed form solutions for
Soulez, Ferréol +5 more
openaire +4 more sources
Analysis of non-iterative phase retrieval based on machine learning
Optical Review, 2020 In this paper, we analyze a machine-learning-based non-iterative phase retrieval method. Phase retrieval and its applications have been attractive research topics in optics and photonics, for example, in biomedical imaging, astronomical imaging, and so ...
Yohei Nishizaki +4 more
semanticscholar +1 more source
Learning to synthesize: robust phase retrieval at low photon counts [PDF]
Light: Science & Applications, 2019 The quality of inverse problem solutions obtained through deep learning is limited by the nature of the priors learned from examples presented during the training phase.
Mo Deng +4 more
semanticscholar +1 more source
Solving systems of phaseless equations via Kaczmarz methods: A proof of concept study [PDF]
, 2015 We study the Kaczmarz methods for solving systems of quadratic equations, i.e., the generalized phase retrieval problem. The methods extend the Kaczmarz methods for solving systems of linear equations by integrating a phase selection heuristic in each ...
Wei, Ke
core +1 more source
Phase retrieval by hyperplanes
, 2017 We show that a scalable frame does phase retrieval if and only if the hyperplanes of its orthogonal complements do phase retrieval. We then show this result fails in general by giving an example of a frame for $\mathbb R^3$ which does phase retrieval but
Botelho-Andrade, Sara +6 more
core +1 more source
IEEE Transactions on Information TheoryTo appear in IEEE Transactions on Information Theory, 2024, 33 pages, 10 ...
Mengchu Xu, Dekuan Dong, Jian Wang
openaire +2 more sources