Video super-resolution reconstruction method based on deep Back projection and motion feature fusion

How to effectively utilize inter-frame redundancies is the key to improve the accuracy and speed of video super-resolution reconstruction methods. Previous methods usually process every frame in the whole video in the same way, and do not make full use of redundant information between frames, result...

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Bibliographic Details
Published in:Multimedia tools and applications 2021-03, Vol.80 (8), p.11423-11441
Main Authors: Fu, Li-hua, Sun, Xiao-wei, Zhao, Yu, Chen, Ren-jie, Chen, Hui, Zhao, Ru
Format: Article
Language:English
Subjects:
Accuracy
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Frames (data processing)
Multimedia Information Systems
Reconstruction
Special Purpose and Application-Based Systems
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Summary:How to effectively utilize inter-frame redundancies is the key to improve the accuracy and speed of video super-resolution reconstruction methods. Previous methods usually process every frame in the whole video in the same way, and do not make full use of redundant information between frames, resulting in low accuracy or long reconstruction time. In this paper, we propose the idea of reconstructing key frames and non-key frames respectively, and give a video super-resolution reconstruction method based on deep back projection and motion feature fusion. Key-frame reconstruction subnet can obtain key frame features and reconstruction results with high accuracy. For non-key frames, key frame features can be reused by fusing them and motion features, so as to obtain accurate non-key frame features and reconstruction results quickly. Experiments on several public datasets show that the proposed method performs better than the state-of-the-art methods, and has good robustness.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-020-10337-2