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Phase retrieval, the problem of recovering lost phase information from measured intensity alone, is an inverse problem that is widely faced in various imaging modalities ranging from astronomy to nanoscale imaging. The current process of…

Image and Video Processing · Electrical Eng. & Systems 2024-06-12 Henry Chan , Youssef S. G. Nashed , Saugat Kandel , Stephan Hruszkewycz , Subramanian Sankaranarayanan , Ross J. Harder , Mathew J. Cherukara

Information about microscopic objects with features smaller than the diffraction limit is almost entirely lost in a far-field diffraction image but could be partly recovered with data completition techniques. Any such approach critically…

Optics · Physics 2020-11-17 Maria Bancerek , Krzysztof M. Czajkowski , Rafal Kotynski

This paper introduces the method of dynamic mode decomposition (DMD) for robustly separating video frames into background (low-rank) and foreground (sparse) components in real-time. The method is a novel application of a technique used for…

Computer Vision and Pattern Recognition · Computer Science 2014-05-01 Jacob Grosek , J. Nathan Kutz

Forward scatter radar (FSR) has emerged as an effective imaging modality for target detection, utilizing forward scattering (FS) signals to reconstruct two-dimensional shadow profile images of objects. However, real-world FS signals are…

Computational Physics · Physics 2025-08-18 ShuQi Lei , Gan Yu , Yuan Tian , XiaoWei Shao

Observations of the 21cm Epoch of Reionization (EoR) signal are dominated by Galactic and extragalactic foregrounds. The need for foreground removal has led to the development of two main techniques, often referred to as "foreground…

In recent years, neural networks have been used to solve phase retrieval problems in imaging with superior accuracy and speed than traditional techniques, especially in the presence of noise. However, in the context of interferometric…

It was recently shown that the phase retrieval imaging of a sample can be modeled as a simple convolution process. Sometimes, such a convolution depends on physical parameters of the sample which are difficult to estimate a priori. In this…

Numerical Analysis · Mathematics 2017-02-20 Eduardo X. Miqueles , Nathaly L. Archilha , Marcelo R. Dos Anjos , Harry Westfahl , Elias S. Helou

In this paper, we present a new policy gradient (PG) methods, namely the block policy mirror descent (BPMD) method for solving a class of regularized reinforcement learning (RL) problems with (strongly)-convex regularizers. Compared to the…

Machine Learning · Computer Science 2022-09-20 Guanghui Lan , Yan Li , Tuo Zhao

X-ray phase-contrast tomography (XPCT) is widely used for high contrast 3D imaging using either synchrotron or laboratory microfocus X-ray sources. XPCT enables an order of magnitude improvement in image contrast of the reconstructed…

Image and Video Processing · Electrical Eng. & Systems 2024-10-28 K. Aditya Mohan , Jean-Baptiste Forien , Venkatesh Sridhar , Jefferson A. Cuadra , Dilworth Parkinson

Given underdetermined measurements of a Positive Semi-Definite (PSD) matrix $X$ of known low rank $K$, we present a new algorithm to estimate $X$ based on recent advances in non-convex optimization schemes. We apply this in particular to…

Optimization and Control · Mathematics 2020-01-29 Marcus Carlsson , Daniele Gerosa

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…

Image and Video Processing · Electrical Eng. & Systems 2025-01-20 Cagatay Isil , Figen S. Oktem

In this paper, we present a dimension reduction method to reduce the dimension of parameter space and state space and efficiently solve inverse problems. To this end, proper orthogonal decomposition (POD) and radial basis function (RBF) are…

Numerical Analysis · Mathematics 2016-10-18 Fuchen Chen , Lijian Jiang , Guanghui Zheng

The problem of phase retrieval, i.e., the problem of recovering a function from the magnitudes of its Fourier transform, naturally arises in various fields of physics, such as astronomy, radar, speech recognition, quantum mechanics and,…

Functional Analysis · Mathematics 2020-02-17 Philipp Grohs , Sarah Koppensteiner , Martin Rathmair

Direct ptychography enables the retrieval of information encoded in the phase of an electron wave passing through a thin sample by deconvolving the interference effects of a converged probe with known aberrations. Under the weak phase…

Phase retrieval, a long-established challenge for recovering a complex-valued signal from its Fourier intensity measurements, has attracted significant interest because of its far-flung applications in optical imaging. To enhance accuracy,…

Signal Processing · Electrical Eng. & Systems 2023-05-16 Qiuliang Ye , Bingo Wing-Kuen Ling , Li-Wen Wang , Daniel Pak-Kong Lun

In this paper, we report the development of the generalized proximal smoothing (GPS) algorithm for phase retrieval of noisy data. GPS is a optimization-based algorithm, in which we relax both the Fourier magnitudes and object constraints.…

Optimization and Control · Mathematics 2019-02-20 Minh Pham , Penghang Yin , Arjun Rana , Stanley Osher , Jiawei Miao

The paper considers the problem of identifying the sparse different components between two high dimensional means of column-wise dependent random vectors. We show that the dependence can be utilized to lower the identification boundary for…

Methodology · Statistics 2014-10-13 Jun Li , Ping-Shou Zhong

The problem of phase retrieval, or the algorithmic recovery of lost phase information from measured intensity alone, underlies various imaging methods from astronomy to nanoscale imaging. Traditional methods of phase retrieval are iterative…

The removal of the Galactic and extragalactic foregrounds remains a major challenge for those wishing to make a detection of the Epoch of Reionization 21-cm signal. Multiple methods of modelling these foregrounds with varying levels of…

Cosmology and Nongalactic Astrophysics · Physics 2016-09-13 Emma Chapman , Saleem Zaroubi , Filipe Abdalla , Fred Dulwich , Vibor Jelić , Benjamin Mort

We present new policy mirror descent (PMD) methods for solving reinforcement learning (RL) problems with either strongly convex or general convex regularizers. By exploring the structural properties of these overall highly nonconvex…

Machine Learning · Computer Science 2022-04-08 Guanghui Lan
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