Multiple CR Spatiotemporal Compressive Imaging System

Higher spatial and temporal resolutions are two important performance parameters in an imaging system. However, due to hardware limitations, the two resolutions are usually mutually restricted. To meet this challenge, we propose a spatiotemporal compressive imaging (STCI) system to reconstruct high-...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiaowen Hao, Dingaoyu Zhao, Jun Ke
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/25/5/1334
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850052692719697920
author Xiaowen Hao
Dingaoyu Zhao
Jun Ke
author_facet Xiaowen Hao
Dingaoyu Zhao
Jun Ke
author_sort Xiaowen Hao
collection DOAJ
description Higher spatial and temporal resolutions are two important performance parameters in an imaging system. However, due to hardware limitations, the two resolutions are usually mutually restricted. To meet this challenge, we propose a spatiotemporal compressive imaging (STCI) system to reconstruct high-spatiotemporal-resolution images from low-resolution measurements. For STCI, we also designed a novel reconstruction network for multiple compression ratio (CR). To verify the effectiveness of our method, we implemented simulation and optical experiments, respectively. The experiment results show that our method can effectively reconstruct high-spatiotemporal-resolution target scenes for nine different CRs. With the maximum spatiotemporal CR of 128:1, our method can achieve a reconstruction accuracy of 28.28 dB.
format Article
id doaj-art-8ece4dc99fe146e09df98d98b0e82241
institution DOAJ
issn 1424-8220
language English
publishDate 2025-02-01
publisher MDPI AG
record_format Article
series Sensors
spelling doaj-art-8ece4dc99fe146e09df98d98b0e822412025-08-20T02:52:45ZengMDPI AGSensors1424-82202025-02-01255133410.3390/s25051334Multiple CR Spatiotemporal Compressive Imaging SystemXiaowen Hao0Dingaoyu Zhao1Jun Ke2School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaHigher spatial and temporal resolutions are two important performance parameters in an imaging system. However, due to hardware limitations, the two resolutions are usually mutually restricted. To meet this challenge, we propose a spatiotemporal compressive imaging (STCI) system to reconstruct high-spatiotemporal-resolution images from low-resolution measurements. For STCI, we also designed a novel reconstruction network for multiple compression ratio (CR). To verify the effectiveness of our method, we implemented simulation and optical experiments, respectively. The experiment results show that our method can effectively reconstruct high-spatiotemporal-resolution target scenes for nine different CRs. With the maximum spatiotemporal CR of 128:1, our method can achieve a reconstruction accuracy of 28.28 dB.https://www.mdpi.com/1424-8220/25/5/1334high-speed high-resolution imagingspatiotemporal compressive imagingcomputational imaging
spellingShingle Xiaowen Hao
Dingaoyu Zhao
Jun Ke
Multiple CR Spatiotemporal Compressive Imaging System
Sensors
high-speed high-resolution imaging
spatiotemporal compressive imaging
computational imaging
title Multiple CR Spatiotemporal Compressive Imaging System
title_full Multiple CR Spatiotemporal Compressive Imaging System
title_fullStr Multiple CR Spatiotemporal Compressive Imaging System
title_full_unstemmed Multiple CR Spatiotemporal Compressive Imaging System
title_short Multiple CR Spatiotemporal Compressive Imaging System
title_sort multiple cr spatiotemporal compressive imaging system
topic high-speed high-resolution imaging
spatiotemporal compressive imaging
computational imaging
url https://www.mdpi.com/1424-8220/25/5/1334
work_keys_str_mv AT xiaowenhao multiplecrspatiotemporalcompressiveimagingsystem
AT dingaoyuzhao multiplecrspatiotemporalcompressiveimagingsystem
AT junke multiplecrspatiotemporalcompressiveimagingsystem