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Fraunhofer diffraction is a well-known phenomenon achieved with most wavelength even without lens. A single-shot intensity measurement of diffraction is generally considered inadequate to reconstruct the original light field, because the…

Image and Video Processing · Electrical Eng. & Systems 2019-12-04 An-Dong Xiong , Xiao-Peng Jin , Wen-Kai Yu , Qing Zhao

As technology grows, higher frequency signals are required to be processed in various applications. In order to digitize such signals, conventional analog to digital convertors are facing implementation challenges due to the higher sampling…

Information Theory · Computer Science 2014-11-27 Amir Zandieh , Alireza Zareian , Masoumeh Azghani , Farokh Marvasti

Quantitative phase imaging has become a topic of considerable interest in the microscopy community. We have recently described one such technique based on the use of a partitioned detection aperture, which can be operated in a single shot…

Optics · Physics 2015-10-20 Roman Barankov , Jean-Charles Baritaux , Jerome Mertz

This paper addresses the problem of sparse phase retrieval, a fundamental inverse problem in applied mathematics, physics, and engineering, where a signal need to be reconstructed using only the magnitude of its transformation while phase…

Machine Learning · Statistics 2025-04-15 The Tien Mai

A new algorithm is developed to jointly recover a temporal sequence of images from noisy and under-sampled Fourier data. Specifically, we consider the case where each data set is missing vital information that prevents its (individual)…

Numerical Analysis · Mathematics 2022-05-13 Yao Xiao , Jan Glaubitz , Anne Gelb , Guohui Song

In this letter we study the subwavelength imaging of sparse broadband sources inside a disordered medium by processing the data acquired by a single antenna. A mathematical model has been developed for solving such problem based on the idea…

Optics · Physics 2015-06-18 Lianlin Li , Fang Li , Tie Jun Cui

In this paper, we propose a novel algorithm for analysis-based sparsity reconstruction. It can solve the generalized problem by structured sparsity regularization with an orthogonal basis and total variation regularization. The proposed…

Computer Vision and Pattern Recognition · Computer Science 2015-04-29 Chen Chen , Junzhou Huang , Lei He , Hongsheng Li

Coded aperture snapshot spectral imaging (CASSI) makes it possible to recover 3D hyperspectral data from a single 2D image. However, the reconstruction problem is severely underdetermined and efforts to improve the compression ratio…

Optics · Physics 2022-08-03 Jiri Hlubucek , Jakub Lukes , Jan Vaclavik , Karel Zidek

A compressed sensing scheme for near-field imaging of corrugations of relative sparse Fourier components is proposed. The scheme employs random sparse measurement of near field to recover the angular spectrum of the scattered field. It is…

Optics · Physics 2015-05-30 Albert Fannjiang , Hsiao-Chieh Tseng

We report a simple fiber-implemented technique for complete reconstruction of intensity profile and phase of ultrashort laser pulses based on processing only pulse spectrum and two self-phase modulated spectra measured after a short piece…

Optics · Physics 2017-12-12 E. A. Anashkina , A. V. Andrianov , M. Yu. Koptev , A. V. Kim

We demonstrate a novel imaging approach and associated reconstruction algorithm for far-field coherent diffractive imaging, based on the measurement of a pair of laterally sheared diffraction patterns. The differential phase profile…

Optics · Physics 2018-05-23 G. S. M. Jansen , A. C. C. de Beurs , X. Liu , K. S. E. Eikema , S. Witte

We consider the problem of reconstructing a HxWx31 hyperspectral image from a HxW grayscale snapshot measurement that is captured using only a single diffractive optic and a filterless panchromatic photosensor. This problem is severely…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Dean Hazineh , Federico Capasso , Todd Zickler

Although several optical techniques have been recently developed in order to overcome the resolution limit in microscopy, the imaging of sub-wavelength features is still a real challenge. In practise, super-resolution techniques remain…

Physics Education · Physics 2019-07-24 Stephane Perrin , Keshia Badu , Paul Montgomery , Sylvain Lecler

In this paper, we discuss application of iterative Stochastic Optimization routines to the problem of sparse signal recovery from noisy observation. Using Stochastic Mirror Descent algorithm as a building block, we develop a multistage…

Machine Learning · Statistics 2022-03-31 Anatoli Juditsky , Andrei Kulunchakov , Hlib Tsyntseus

This paper presents a Multispectral imaging (MSI) approach that combines the use of a diffractive optical element, and a deep learning algorithm for spectral reconstruction. Traditional MSI techniques often face challenges such as high…

Image and Video Processing · Electrical Eng. & Systems 2023-10-06 Khen Cohen , Tuval Kay

Two complementary approaches have been extensively used in signal and image processing leading to novel results, the sparse representation methodology and the variational strategy. Recently, a new sparsity based model has been proposed, the…

Computer Vision and Pattern Recognition · Computer Science 2015-08-17 Raja Giryes , Michael Elad , Alfred M. Bruckstein

As conventional frame-based cameras suffer from high energy consumption and latency, several new types of image sensors have been devised, with some of them exploiting the sparsity of natural images in some transform domains. Instead of…

Applied Physics · Physics 2021-09-30 Lukas Mennel , Dmitry K. Polyushkin , Dohyun Kwak , Thomas Mueller

This paper proposes an image interpolation algorithm exploiting sparse representation for natural images. It involves three main steps: (a) obtaining an initial estimate of the high resolution image using linear methods like FIR filtering,…

Computer Vision and Pattern Recognition · Computer Science 2013-08-07 H. Lakshman , W. -Q Lim , H. Schwarz , D. Marpe , G. Kutyniok , T. Wiegand

Recovery of arbitrarily positioned samples that are missing in sparse signals recently attracted significant research interest. Sparse signals with heavily corrupted arbitrary positioned samples could be analyzed in the same way as…

Information Theory · Computer Science 2013-09-24 Ljubisa Stankovic , Milos Dakovic , Stefan Vujovic