Snapshot multiplexed imaging based on compressive sensing

Ying Fu, Chen Sun, Lizhi Wang, Hua Huang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Multiplexed imaging methods have been proposed to extend the field of view (FoV) of the imaging devices. However, the nature of multiple exposures hinders its application in time-crucial scenarios. In this paper, we design a snapshot multiplexed imaging system for wide FoV imaging. In the system, the scene is first spatially encoded by a mask, and then the coded scene is optically divided into multiple sub-regions which are finally superimposed and measured on a sensor array. We model the demultiplexing as a compressive sensing (CS) reconstruction problem and introduce two methods, one is based on Total Variation (TV) constraint and the other is based on sparsity constraint, to reconstruct the scene. Simulation results demonstrate the effectiveness of the proposed system.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing – PCM 2018 - 19th Pacific-Rim Conference on Multimedia, 2018, Proceedings
EditorsWen-Huang Cheng, Toshihiko Yamasaki, Chong-Wah Ngo, Richang Hong, Meng Wang
PublisherSpringer Verlag
Pages465-475
Number of pages11
ISBN (Print)9783030007669
DOIs
Publication statusPublished - 2018
Event19th Pacific-Rim Conference on Multimedia, PCM 2018 - Hefei, China
Duration: 21 Sept 201822 Sept 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11165 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th Pacific-Rim Conference on Multimedia, PCM 2018
Country/TerritoryChina
CityHefei
Period21/09/1822/09/18

Keywords

  • CS
  • Multiplexed imaging
  • Snapshot
  • Wide FoV

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