Fast LiDAR imaging of sparse targets with compressive Hadamard samples

Vladislav Kravets; Adrian Stern

Fast LiDAR imaging of sparse targets with compressive Hadamard samples

Vladislav Kravets
, Adrian Stern

Research output: Contribution to journal › Conference article › peer-review

Abstract

An efficient adaptive sensing technique for LiDAR imaging of sparse targets with a Hadamard sensing matrix is introduced. A fast, real-time reconstruction is performed by a convolutional neural network.

Original language	English
Article number	DF3A.5
Journal	Optics InfoBase Conference Papers
State	Published - 1 Jan 2020
Event	3D Image Acquisition and Display: Technology, Perception and Applications, 3D 2020 - Part of Imaging and Applied Optics Congress - Virtual, Online, United States Duration: 22 Jun 2020 → 26 Jun 2020

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Mechanics of Materials

Cite this

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title = "Fast LiDAR imaging of sparse targets with compressive Hadamard samples",

abstract = "An efficient adaptive sensing technique for LiDAR imaging of sparse targets with a Hadamard sensing matrix is introduced. A fast, real-time reconstruction is performed by a convolutional neural network.",

author = "Vladislav Kravets and Adrian Stern",

note = "Publisher Copyright: {\textcopyright} OSA 2020, {\textcopyright} 2020 The Author(s).; 3D Image Acquisition and Display: Technology, Perception and Applications, 3D 2020 - Part of Imaging and Applied Optics Congress ; Conference date: 22-06-2020 Through 26-06-2020",

year = "2020",

month = jan,

day = "1",

language = "English",

journal = "Optics InfoBase Conference Papers",

issn = "2162-2701",

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TY - JOUR

T1 - Fast LiDAR imaging of sparse targets with compressive Hadamard samples

AU - Kravets, Vladislav

AU - Stern, Adrian

PY - 2020/1/1

Y1 - 2020/1/1

N2 - An efficient adaptive sensing technique for LiDAR imaging of sparse targets with a Hadamard sensing matrix is introduced. A fast, real-time reconstruction is performed by a convolutional neural network.

AB - An efficient adaptive sensing technique for LiDAR imaging of sparse targets with a Hadamard sensing matrix is introduced. A fast, real-time reconstruction is performed by a convolutional neural network.

UR - https://www.scopus.com/pages/publications/85118614510

M3 - Conference article

SN - 2162-2701

JO - Optics InfoBase Conference Papers

JF - Optics InfoBase Conference Papers

M1 - DF3A.5

T2 - 3D Image Acquisition and Display: Technology, Perception and Applications, 3D 2020 - Part of Imaging and Applied Optics Congress

Y2 - 22 June 2020 through 26 June 2020

ER -

Fast LiDAR imaging of sparse targets with compressive Hadamard samples

Abstract

ASJC Scopus subject areas

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