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Multiple light scattering hampers imaging objects in complex scattering media. Approaches used in real practices mainly aim to filter out multiple scattering obscuring the ballistic waves that travel straight through the scattering medium.…

This work reveals an experimental microscopy acquisition scheme successfully combining Compressed Sensing (CS) and digital holography in off-axis and frequency-shifting conditions. CS is a recent data acquisition theory involving signal…

The numerical analysis of elastic wave propagation in unbounded media may be difficult due to spurious waves reflected at the model artificial boundaries. This point is critical for the analysis of wave propagation in heterogeneous or…

Computational Physics · Physics 2010-09-07 Jean-François Semblat , Luca Lenti , Ali Gandomzadeh

A compressive sensing based circular polarization snapshot spectral imaging system is proposed in this paper to acquire two-dimensional spatial, one-dimensional circular polarization (the right and left circular polarization), and…

We derive and discuss general physical bounds on the electromagnetic scattering and absorption of passive structures. Our theory, based on passivity and power conservation, quantifies the minimum and maximum allowed scattering for an object…

Optics · Physics 2015-06-17 Romain Fleury , Jason Soric , Andrea Alu

Compressive Sensing (CS) is a new technique for the efficient acquisition of signals, images, and other data that have a sparse representation in some basis, frame, or dictionary. By sparse we mean that the N-dimensional basis…

Information Theory · Computer Science 2015-05-18 Chinmay Hegde , Richard G. Baraniuk

We provide two novel adaptive-rate compressive sensing (CS) strategies for sparse, time-varying signals using side information. Our first method utilizes extra cross-validation measurements, and the second one exploits extra low-resolution…

Computer Vision and Pattern Recognition · Computer Science 2023-07-19 Garrett Warnell , Sourabh Bhattacharya , Rama Chellappa , Tamer Basar

Existing three-dimensional (3-D) compressive sensing-based millimeter-wave (MMW) imaging methods require a large-scale storage of the sensing matrix and immense computations owing to the high dimension matrix-vector model employed in the…

Signal Processing · Electrical Eng. & Systems 2018-12-26 Shiyong Li , Guoqiang Zhao , Houjun Sun , Moeness Amin

Optical systems which measure independent random projections of a scene according to compressed sensing (CS) theory face a myriad of practical challenges related to the size of the physical platform, photon efficiency, the need for high…

Applications · Statistics 2015-03-19 Zachary T. Harmany , Roummel F. Marcia , Rebecca M. Willett

Super-resolution imaging with advanced optical systems has been revolutionizing technical analysis in various fields from biological to physical sciences. However, many objects are hidden by strongly scattering media such as rough wall…

Optics · Physics 2021-09-06 Dong Wang , Sujit Kumar Sahoo , Cuong Dang

We study active array imaging of small but strong scatterers in homogeneous media when multiple scattering between them is important. We use the Foldy-Lax equations to model wave propagation with multiple scattering when the scatterers are…

Mathematical Physics · Physics 2015-12-15 Anwei Chai , Miguel Moscoso , George Papanicolaou

Waves scattered by a weakly inhomogeneous random medium contain a predominant single scattering contribution as well as a multiple scattering contribution which is usually neglected, especially for imaging purposes. A method based on random…

Classical Physics · Physics 2015-03-13 Alexandre Aubry , Arnaud Derode

Compressive sampling is a new paradigm for sampling, based on sparseness of signals or signal representations. It is much less restrictive than Nyquist-Shannon sampling theory and thus explains and systematises the widespread experience…

Instrumentation and Methods for Astrophysics · Physics 2015-05-28 Feng Li , Tim J. Cornwell , Frank de Hoog

The potential of compressed sensing for obtaining sparse time-frequency representations for gravitational wave data analysis is illustrated by comparison with existing methods, as regards i) shedding light on the fine structure of noise…

Instrumentation and Methods for Astrophysics · Physics 2016-05-16 Paolo Addesso , Maurizio Longo , Stefano Marano , Vincenzo Matta , Maria Principe , Innocenzo M. Pinto

This letter proposes a novel distributed compressed estimation scheme for sparse signals and systems based on compressive sensing techniques. The proposed scheme consists of compression and decompression modules inspired by compressive…

Information Theory · Computer Science 2015-02-05 S. Xu , R. C. de Lamare , H. V. Poor

Image classification is a core task of intelligent sensing, conventionally follows a sequential imaging then processing pipeline. However, redundant high-dimensional image reconstruction is inherently inefficient, especially in photon…

Compressed sensing is an image reconstruction technique to achieve high-quality results from limited amount of data. In order to achieve this, it utilizes prior knowledge about the samples that shall be reconstructed. Focusing on image…

We suggest scattering experiments which implement the concept of ``protective measurements'' allowing the measurement of the complete wave function even when only one quantum system (rather than an ensemble) is available. Such scattering…

Quantum Physics · Physics 2009-10-30 S. Nussinov

Optical wavefront-shaping has emerged as a powerful tool to manipulate light in strongly scattering media. It enables diffraction-limited focusing and imaging at depths where conventional microscopy techniques fail. However, while most…

Optics · Physics 2014-03-04 T. Chaigne , O. Katz , A. C. Boccara , M. Fink , E. Bossy , S. Gigan

This paper demonstrates how new principles of compressed sensing, namely asymptotic incoherence, asymptotic sparsity and multilevel sampling, can be utilised to better understand underlying phenomena in practical compressed sensing and…

Functional Analysis · Mathematics 2014-07-08 Bogdan Roman , Anders Hansen , Ben Adcock
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