Research on region selection super resolution restoration algorithm based on infrared micro-scanning optical imaging model

Abstract With spring up of infrared imaging related industry, infrared imaging technology has become mainstream development direction of intelligent photoelectrical detection due to its good concealment, wide detection range, high positioning accuracy, long distant penetration, light weight, little...

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Autores principales:	Jian Chen, Yan Li, LiHua Cao
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3e8a503734a149c5947d91d95c474f34
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spelling	oai:doaj.org-article:3e8a503734a149c5947d91d95c474f342021-12-02T10:44:08ZResearch on region selection super resolution restoration algorithm based on infrared micro-scanning optical imaging model10.1038/s41598-021-82119-12045-2322https://doaj.org/article/3e8a503734a149c5947d91d95c474f342021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82119-1https://doaj.org/toc/2045-2322Abstract With spring up of infrared imaging related industry, infrared imaging technology has become mainstream development direction of intelligent photoelectrical detection due to its good concealment, wide detection range, high positioning accuracy, long distant penetration, light weight, little volume, low power dissipation and high solidity. However, the features of infrared dim-small target image such as less details and low SNR become bottleneck of infrared image application. How to enhance imaging effect of infrared dim-small target becomes research hotspot. Starting from the point of ‘restoration as foundation’, the theory and technology of infrared dim-small target super-resolution restoration by utilizing the theory and technology of super-resolution restoration are explored in this paper. This paper mainly focuses on the research of super-resolution restoration algorithm of infrared dim-small target based on infrared micro-scanning optical model. Aiming at solving super-resolution restoration problem of infrared dim-small target, the traditional super-resolution restoration algorithm is optimized and the improved algorithm is proposed. Meanwhile, infrared micro-scanning optical model is introduced to break theoretical limit of simple image processing algorithm. And the performance of infrared image super-resolution restoration is improved.Jian ChenYan LiLiHua CaoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jian Chen Yan Li LiHua Cao Research on region selection super resolution restoration algorithm based on infrared micro-scanning optical imaging model
description	Abstract With spring up of infrared imaging related industry, infrared imaging technology has become mainstream development direction of intelligent photoelectrical detection due to its good concealment, wide detection range, high positioning accuracy, long distant penetration, light weight, little volume, low power dissipation and high solidity. However, the features of infrared dim-small target image such as less details and low SNR become bottleneck of infrared image application. How to enhance imaging effect of infrared dim-small target becomes research hotspot. Starting from the point of ‘restoration as foundation’, the theory and technology of infrared dim-small target super-resolution restoration by utilizing the theory and technology of super-resolution restoration are explored in this paper. This paper mainly focuses on the research of super-resolution restoration algorithm of infrared dim-small target based on infrared micro-scanning optical model. Aiming at solving super-resolution restoration problem of infrared dim-small target, the traditional super-resolution restoration algorithm is optimized and the improved algorithm is proposed. Meanwhile, infrared micro-scanning optical model is introduced to break theoretical limit of simple image processing algorithm. And the performance of infrared image super-resolution restoration is improved.
format	article
author	Jian Chen Yan Li LiHua Cao
author_facet	Jian Chen Yan Li LiHua Cao
author_sort	Jian Chen
title	Research on region selection super resolution restoration algorithm based on infrared micro-scanning optical imaging model
title_short	Research on region selection super resolution restoration algorithm based on infrared micro-scanning optical imaging model
title_full	Research on region selection super resolution restoration algorithm based on infrared micro-scanning optical imaging model
title_fullStr	Research on region selection super resolution restoration algorithm based on infrared micro-scanning optical imaging model
title_full_unstemmed	Research on region selection super resolution restoration algorithm based on infrared micro-scanning optical imaging model
title_sort	research on region selection super resolution restoration algorithm based on infrared micro-scanning optical imaging model
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3e8a503734a149c5947d91d95c474f34
work_keys_str_mv	AT jianchen researchonregionselectionsuperresolutionrestorationalgorithmbasedoninfraredmicroscanningopticalimagingmodel AT yanli researchonregionselectionsuperresolutionrestorationalgorithmbasedoninfraredmicroscanningopticalimagingmodel AT lihuacao researchonregionselectionsuperresolutionrestorationalgorithmbasedoninfraredmicroscanningopticalimagingmodel
_version_	1718396821617770496

Research on region selection super resolution restoration algorithm based on infrared micro-scanning optical imaging model

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