Atmospheric Turbulence Removal in Long-Range Imaging Using a Data-Driven-Based Approach

Atmospheric turbulence is one of the causes of quality degradation in long-range imaging and its removal from degraded frame sequences is considered an ill-posed problem. There have been numerous attempts to address this problem. However, there is still room for improving the quality of the restored...

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Vydáno v:	International journal of computer vision Ročník 130; číslo 4; s. 1031 - 1049
Hlavní autoři:	Fazlali, Hamidreza, Shirani, Shahram, BradforSd, Michael, Kirubarajan, Thia
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.04.2022 Springer Springer Nature B.V
Témata:	Artificial Intelligence Atmospheric turbulence Buildings Cameras Cluster analysis Clustering Coders Computer Imaging Computer Science Feature extraction Frames Ill posed problems Image contrast Image Processing and Computer Vision Image quality Image reconstruction Image restoration Methods Pattern Recognition Pattern Recognition and Graphics Registration Remodeling, restoration, etc Salience Search algorithms Turbulence Vector quantization Vision Deep learning means Binary search Atmospheric turbulence Autoencoder Long-range imaging Saliency map Fusion
ISSN:	0920-5691, 1573-1405
On-line přístup:	Získat plný text
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