No-Reference Quality Assessment of Extended Target Adaptive Optics Images Using Deep Neural Network
No-Reference Quality Assessment of Extended Target Adaptive Optics Images Using Deep Neural Network
About this item
Full title
Author / Creator
Gao, Guoqing , Li, Lingxiao , Chen, Hao , Jiang, Ning , Li, Shuqi , Bian, Qing , Bao, Hua and Rao, Changhui
Publisher
Switzerland: MDPI AG
Journal title
Language
English
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Publication information
Publisher
Switzerland: MDPI AG
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Scope and Contents
Contents
This paper proposes a supervised deep neural network model for accomplishing highly efficient image quality assessment (IQA) for adaptive optics (AO) images. The AO imaging systems based on ground-based telescopes suffer from residual atmospheric turbulence, tracking error, and photoelectric noise, which can lead to varying degrees of image degrada...
Alternative Titles
Full title
No-Reference Quality Assessment of Extended Target Adaptive Optics Images Using Deep Neural Network
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_85fb26f9f56c4998831f45e990c41461
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_85fb26f9f56c4998831f45e990c41461
Other Identifiers
ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s24010001
