Title
Satellite Video Super-Resolution Based on Adaptively Spatiotemporal Neighbors and Nonlocal Similarity Regularization
Abstract
Recently, super-resolution (SR) of satellite videos has received increasing attention as it can overcome the limitation of spatial resolution in applications of satellite videos to dynamic analysis. The low quality of satellite videos presents big challenges to the development of the spatial SR techniques, e.g., accurate motion estimation and motion compensation for multiframe SR. Therefore, reasonable image priors in maximum a posteriori (MAP) framework, where motion information among adjacent frames is involved, are needed to regularize the solution space and generate the corresponding high-resolution frames. In this article, an effective satellite video SR framework based on locally spatiotemporal neighbors and nonlocal similarity modeling is proposed. Firstly, local prior knowledge is represented by means of adaptively exploiting spatiotemporal neighbors. In this way, implicitly local motion information can be captured without explicit motion estimation. Secondly, the nonlocal spatial similarity is integrated into the proposed SR framework to enhance texture details. Finally, the locally spatiotemporal regularization and nonlocal similarity modeling bring out a complex optimization problem, which is solved via the iterated reweighted least squares in the proposed SR framework. The videos from the Jilin-1 satellite and the OVS-1A satellite are used for evaluating the proposed method. Experimental results show that the proposed method demonstrates better SR performance in preserving edges and texture details compared with the-state-of-art video SR methods.
Year
DOI
Venue
2020
10.1109/TGRS.2020.2987400
IEEE Transactions on Geoscience and Remote Sensing
Keywords
DocType
Volume
Adaptively spatiotemporal neighbors,implicit motion estimation,maximum a posteriori (MAP),nonlocal similarity,satellite video,super-resolution (SR)
Journal
58
Issue
ISSN
Citations 
12
0196-2892
1
PageRank 
References 
Authors
0.35
0
4
Name
Order
Citations
PageRank
Huan Liu1182.27
Yanfeng Gu274255.56
Tengfei Wang343.45
Shengyang Li4116.65