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Compressive sensing has been used to demonstrate scene reconstruction and source localization in a wide variety of devices. To date, optical compressive sensors have not been able to achieve significant volume reduction relative to…

Imaging through a single optical fiber offers attractive possibilities in many applications such as microendoscopy or remote sensing. However, the direct transmission of an image through an optical fiber is difficult because spatial…

Optics · Physics 2015-05-29 Roman Barankov , Jerome Mertz

We demonstrate a multi-beam scanning transmission electron microscopy (STEM) imaging that integrates down-sampling with super-resolution image reconstruction via a compressive sensing framework. A custom condenser aperture with six randomly…

Instrumentation and Detectors · Physics 2026-03-19 Akira Yasuhara , Takumi Sannomiya , Ryoichi Horisaki

Polarization imaging is a technique that creates a pixel map of the polarization state in a scene. Although invisible to the human eye, polarization can assist various sensing and computer vision tasks. Existing polarization cameras use…

Image and Video Processing · Electrical Eng. & Systems 2026-03-19 Noa Kraicer , Shay Elmalem , Erez Yosef , Hani Barhum , Raja Giryes

Femtosecond spectroscopy is an important tool for tracking rapid photoinduced processes in a variety of materials. To spatially map the processes in a sample would substantially expand the capabilities of the method. This is, however,…

Optics · Physics 2019-05-01 Ondřej Denk , Kaibo Zheng , Donatas Zigmantas , Karel Žídek

Compressive Learning is an emerging topic that combines signal acquisition via compressive sensing and machine learning to perform inference tasks directly on a small number of measurements. Many data modalities naturally have a…

Computer Vision and Pattern Recognition · Computer Science 2020-10-22 Dat Thanh Tran , Mehmet Yamac , Aysen Degerli , Moncef Gabbouj , Alexandros Iosifidis

The interest of compressive sampling in ultrasound imaging has been recently extensively evaluated by several research teams. Following the different application setups, it has been shown that the RF data may be reconstructed from a small…

Computer Vision and Pattern Recognition · Computer Science 2015-12-07 Zhouye Chen , Adrian Basarab , Denis Kouamé

Compressed sensing (CS) is an innovative technique allowing to represent signals through a small number of their linear projections. In this paper we address the application of CS to the scenario of progressive acquisition of 2D visual…

Information Theory · Computer Science 2014-03-06 Giulio Coluccia , Enrico Magli

X-Ray Fluorescence (XRF) scanning is a widespread technique of high importance and impact since it provides chemical composition maps crucial for several scientific investigations. There are continuous requirements for larger, faster and…

Data Analysis, Statistics and Probability · Physics 2020-05-13 George Kourousias , Fulvio Billè , Roberto Borghes , Antonio Alborini , Simone Sala , Roberto Alberti , Alessandra Gianoncelli

We suggest a novel scheme for generating multimode squeezed states for the boson sampling implementation. The idea is to replace a commonly used linear interferometer by a multimode resonator containing a passive optical element consisting…

Quantum Physics · Physics 2024-09-16 Sergey V. Tarasov , Vladimir V. Kocharovsky

Microscopes face a trade-off between spatial resolution, field-of-view, and frame rate -- improving one of these properties typically requires sacrificing the others, due to the limited spatiotemporal throughput of the sensor. To overcome…

Fluorescence microscopy has been a significant tool to observe long-term imaging of embryos (in vivo) growth over time. However, cumulative exposure is phototoxic to such sensitive live samples. While techniques like light-sheet…

Image and Video Processing · Electrical Eng. & Systems 2022-01-05 Varun Mannam , Jacob Brandt , Cody J. Smith , Scott Howard

Lensless fiber endomicroscope is an emerging tool for in-vivo microscopic imaging, where quantitative phase imaging (QPI) can be utilized as a label-free method to enhance image contrast. However, existing single-shot phase reconstruction…

Compressive sensing (CS) combines data acquisition with compression coding to reduce the number of measurements required to reconstruct a sparse signal. In optics, this usually takes the form of projecting the field onto sequences of random…

Information Theory · Computer Science 2018-10-24 Davood Mardani , H. Esat Kondakci , Lane Martin , Ayman F. Abouraddy , George K. Atia

Cryo Focused Ion-Beam Scanning Electron Microscopy (cryo FIB-SEM) enables three-dimensional and nanoscale imaging of biological specimens via a slice and view mechanism. The FIB-SEM experiments are, however, limited by a slow (typically,…

This paper introduces two acquisition device architectures for multispectral compressive imaging. Unlike most existing methods, the proposed computational imaging techniques do not include any dispersive element, as they use a dedicated…

Computer Vision and Pattern Recognition · Computer Science 2018-02-07 Kévin Degraux , Valerio Cambareri , Bert Geelen , Laurent Jacques , Gauthier Lafruit

In biological microscopy, light scattering represents the main limitation to image at depth. Recently, a set of wavefront shaping techniques has been developed in order to manipulate coherent light in strongly disordered materials. The…

Optics · Physics 2021-01-07 Antoine Boniface , Jonathan Dong , Sylvain Gigan

This paper deals with the Compressive Sensing implementation in the Face Recognition problem. Compressive Sensing is new approach in signal processing with a single goal to recover signal from small set of available samples. Compressive…

Computer Vision and Pattern Recognition · Computer Science 2019-02-15 Slavko Kovacevic , Vuko Djaletic , Jelena Vukovic

Measurement of the optical transmission matrix (TM) of an opaque material is an advanced form of space-variant aberration correction. Beyond imaging, TM-based methods are emerging in a range of fields including optical communications,…

We propose a novel framework to automatically learn to aggregate and transform photometric measurements from multiple unstructured views into spatially distinctive and view-invariant low-level features, which are subsequently fed to a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Xiang Feng , Kaizhang Kang , Fan Pei , Huakeng Ding , Jinjiang You , Ping Tan , Kun Zhou , Hongzhi Wu