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Related papers: Phase Retrieval via Wirtinger Flow: Theory and Alg…

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In this paper, we study the affine phase retrieval problem, which aims to recover signals from the magnitudes of affine measurements. We develop second-order optimization methods based on Newton and Gauss-Newton iterations and establish…

Information Theory · Computer Science 2025-04-03 Bing Gao

Zernike's phase contrast microscopy (PCM) is among the most widely used techniques for observing phase objects, but it lacks quantitative nature, as it cannot directly provide phase information. Current methods for computationally…

In this work we propose a nonconvex two-stage \underline{s}tochastic \underline{a}lternating \underline{m}inimizing (SAM) method for sparse phase retrieval. The proposed algorithm is guaranteed to have an exact recovery from $O(s\log n)$…

Numerical Analysis · Mathematics 2022-11-23 Jian-Feng Cai , Yuling Jiao , Xiliang Lu , Juntao You

In many signal processing problems arising in practical applications, we wish to reconstruct an unknown signal from its phaseless measurements with respect to a frame. This inverse problem is known as the phase retrieval problem. For each…

Information Theory · Computer Science 2023-07-04 Palina Salanevich

A novel approach termed \emph{stochastic truncated amplitude flow} (STAF) is developed to reconstruct an unknown $n$-dimensional real-/complex-valued signal $\bm{x}$ from $m$ `phaseless' quadratic equations of the form…

Information Theory · Computer Science 2017-04-05 Gang Wang , Georgios B. Giannakis , Jie Chen

The main aim of this paper is to study quaternion phase retrieval (QPR), i.e., the recovery of quaternion signal from the magnitude of quaternion linear measurements. We show that all $d$-dimensional quaternion signals can be reconstructed…

Signal Processing · Electrical Eng. & Systems 2023-07-25 Junren Chen , Michael K. Ng

Consider a scenario in which an unknown signal is transformed by a known linear operator, and then the pointwise absolute value of the unknown output function is reported. This scenario appears in several applications, and the goal is to…

Information Theory · Computer Science 2014-03-10 Dustin G. Mixon

Phase retrieval, a nonlinear problem prevalent in imaging applications, has been extensively studied using random models, some of which with i.i.d. sensing matrix components. While these models offer robust reconstruction guarantees, they…

Optics · Physics 2024-09-10 Zhiyuan Hu , Julián Tachella , Michael Unser , Jonathan Dong

PhaseLift is a noted convex optimization technique for phase retrieval that can recover a signal exactly from amplitude measurements only, with high probability. Conventional PhaseLift requires a relatively large number of samples that…

Signal Processing · Electrical Eng. & Systems 2022-04-27 Zhe Zhang , Zhi Tian

In this work we consider the problem of reconstruction of a signal from the magnitude of its Fourier transform, also known as phase retrieval. The problem arises in many areas of astronomy, crystallography, optics, and coherent diffraction…

Optics · Physics 2012-03-22 Eliyahu Osherovich

High-throughput computational imaging requires efficient processing algorithms to retrieve multi-dimensional and multi-scale information. In computational phase imaging, phase retrieval (PR) is required to reconstruct both amplitude and…

Image and Video Processing · Electrical Eng. & Systems 2021-09-15 Xuyang Chang , Liheng Bian , Jun Zhang

Phase retrieval has important applications in optical imaging, communications and sensing. Lifting the dimensionality of the problem allows phase retrieval to be approximated as a convex optimization problem in a higher-dimensional space.…

Information Theory · Computer Science 2018-05-09 Sercan O. Arik , Joseph M. Kahn

The current ghost imaging phase reconstruction schemes require either complex optical systems, Fourier transform steps, or iterative algorithms, which may increase the difficulty of system design, cause phase retrieval error or take too…

Optics · Physics 2023-02-09 Ziyan Chen , Heng Wu , Jing Cheng

This paper deals with finding an $n$-dimensional solution $x$ to a system of quadratic equations of the form $y_i=|\langle{a}_i,x\rangle|^2$ for $1\le i \le m$, which is also known as phase retrieval and is NP-hard in general. We put forth…

Optimization and Control · Mathematics 2017-05-31 Gang Wang , Georgios B. Giannakis , Yousef Saad , Jie Chen

Ptychography has risen as a reference X-ray imaging technique: it achieves resolutions of one billionth of a meter, macroscopic field of view, or the capability to retrieve chemical or magnetic contrast, among other features. A…

Optimization and Control · Mathematics 2019-06-10 Huibin Chang , Pable Enfedaque , Stefano Marchesini

Phase-retrieval from coded diffraction patterns (CDP) is important to X-ray crystallography, diffraction tomography and astronomical imaging, yet remains a hard, non-convex inverse problem. We show that CDP recovery can be reformulated…

In this paper, we propose an optimization-based method for robust phase retrieval problem where the goal is to estimate an unknown signal from a quadratic measurement corrupted by outliers. To enhance the robustness of existing optimization…

Optimization and Control · Mathematics 2026-04-17 Kumataro Yazawa , Keita Kume , Isao Yamada

The problem of recovering a vector from the absolute values of its inner products against a family of measurement vectors has been well studied in mathematics and engineering. A generalization of this phase retrieval problem also exists in…

Functional Analysis · Mathematics 2013-07-19 Jameson Cahill , Peter G. Casazza , Jesse Peterson , Lindsey Woodland

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

Phase retrieval algorithms have become an important component in many modern computational imaging systems. For instance, in the context of ptychography and speckle correlation imaging, they enable imaging past the diffraction limit and…

Machine Learning · Statistics 2018-07-03 Christopher A. Metzler , Philip Schniter , Ashok Veeraraghavan , Richard G. Baraniuk