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Related papers: Real-time phase-retrieval and wavefront sensing en…

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We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen…

Materials Science · Physics 2022-02-28 Thomas Friedrich , Chu-Ping Yu , Johan Verbeek , Timothy Pennycook , Sandra Van Aert

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…

Phase reconstruction, which estimates phase from a given amplitude spectrogram, is an active research field in acoustical signal processing with many applications including audio synthesis. To take advantage of rich knowledge from data,…

Audio and Speech Processing · Electrical Eng. & Systems 2020-02-17 Yoshiki Masuyama , Kohei Yatabe , Yuma Koizumi , Yasuhiro Oikawa , Noboru Harada

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…

The reconstruction of phase spaces is an essential step to analyze time series according to Dynamical System concepts. A regression performed on such spaces unveils the relationships among system states from which we can derive their…

Machine Learning · Computer Science 2020-06-23 Lucas Pagliosa , Alexandru Telea , Rodrigo Mello

In Bragg Coherent Diffraction Imaging (BCDI), Phase Retrieval of highly strained crystals is often challenging with standard iterative algorithms. This computational obstacle limits the potential of the technique as it precludes the…

In coherent X-ray diffraction microscopy the diffraction pattern generated by a sample illuminated with coherent x-rays is recorded, and a computer algorithm recovers the unmeasured phases to synthesize an image. By avoiding the use of a…

Existing neural reconstruction schemes such as Neural Radiance Field (NeRF) are largely focused on modeling opaque objects. We present a novel neural refractive field(NeReF) to recover wavefront of transparent fluids by simultaneously…

Computer Vision and Pattern Recognition · Computer Science 2022-03-09 Ziyu Wang , Wei Yang , Junming Cao , Lan Xu , Junqing Yu , Jingyi Yu

Graphics rendering applications increasingly leverage neural networks in tasks such as denoising, supersampling, and frame extrapolation to improve image quality while maintaining frame rates. The temporal coherence inherent in these tasks…

Graphics · Computer Science 2025-06-18 Lufei Liu , Tor M. Aamodt

Optical aberrations prevent telescopes from reaching their theoretical diffraction limit. Once estimated, these aberrations can be compensated for using deformable mirrors in a closed loop. Focal plane wavefront sensing enables the…

In both light optics and electron optics, the amplitude of a wave scattered by an object is an observable that is usually recorded in the form of an intensity distribution in a real space image or a diffraction image. In contrast, retrieval…

One of the most powerful approaches to imaging at the nanometer or subnanometer length scale is coherent diffraction imaging using X-ray sources. For amorphous (non-crystalline) samples, the raw data can be interpreted as the modulus of the…

Numerical Analysis · Mathematics 2020-04-02 Alexander Barnett , Charles L. Epstein , Leslie Greengard , Jeremy Magland

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…

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

Despite the recent popularity of deep generative state space models, few comparisons have been made between network architectures and the inference steps of the Bayesian filtering framework -- with most models simultaneously approximating…

Machine Learning · Statistics 2020-09-29 Bryan Lim , Stefan Zohren , Stephen Roberts

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

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

In this paper, we show that a revised convolutional recurrent neural network (CRNN) can decrease, by orders of magnitude, the time needed for the phase-resolved prediction of waves in a spatiotemporal domain of a nonlinear dispersive wave…

Fluid Dynamics · Physics 2020-08-04 Fazlolah Mohaghegh , Mohammad-Reza Alam , Jayathi Murthy

This paper discusses the noisy phase retrieval problem: recovering a complex image signal with independent noise from quadratic measurements. Inspired by the dark fringes shown in the measured images of the array detector, a novel phase…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Wen-Kai Yu , An-Dong Xiong , Xu-Ri Yao , Guang-Jie Zhai , Qing Zhao

We propose and demonstrate a new phase retrieval method for imaging through random media. Although methods to recover the Fourier amplitude through random distortions are well established, recovery of the Fourier phase has been a more…

Optics · Physics 2021-05-14 Byungjae Hwang , Taeseong Woo , Cheolwoo Ahn , Jung-Hoon Park

This paper considers the question of recovering the phase of an object from intensity-only measurements, a problem which naturally appears in X-ray crystallography and related disciplines. We study a physically realistic setup where one can…

Information Theory · Computer Science 2013-11-08 Emmanuel Candes , Xiaodong Li , Mahdi Soltanolkotabi