Video super-resolution network using detail component extraction and optical flow enhancement algorithm

Applied Intelligence ◽

10.1007/s10489-021-02882-6 ◽

2022 ◽

Author(s):

Zhensen Chen ◽

Wenyuan Yang ◽

Jingmin Yang

Keyword(s):

Optical Flow ◽

Super Resolution ◽

Flow Enhancement ◽

Component Extraction ◽

Enhancement Algorithm

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Attention deep and shallow network union HR optical flow compensation for video super-resolution

Optical Engineering ◽

10.1117/1.oe.60.10.103102 ◽

2021 ◽

Vol 60 (10) ◽

Author(s):

Xuan Zhu ◽

Yuying Jin ◽

Lin Wang ◽

Jun Wang ◽

Zhixiang Lan ◽

...

Keyword(s):

Optical Flow ◽

Super Resolution ◽

Flow Compensation

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Optical flow based super-resolution: A probabilistic approach

Computer Vision and Image Understanding ◽

10.1016/j.cviu.2005.09.011 ◽

2007 ◽

Vol 106 (1) ◽

pp. 106-115 ◽

Author(s):

Rik Fransens ◽

Christoph Strecha ◽

Luc Van Gool

Keyword(s):

Optical Flow ◽

Probabilistic Approach ◽

Super Resolution

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Video super-resolution based on automatic key-frame selection and feature-guided variational optical flow

Signal Processing Image Communication ◽

10.1016/j.image.2014.06.005 ◽

2014 ◽

Vol 29 (8) ◽

pp. 875-886 ◽

Author(s):

Yanming Zhu ◽

Kun Li ◽

Jianmin Jiang

Keyword(s):

Optical Flow ◽

Super Resolution ◽

Frame Selection ◽

Key Frame ◽

Key Frame Selection

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Research on single image super resolution enhancement algorithm based on deep learning

10.1109/phm-nanjing52125.2021.9612927 ◽

2021 ◽

Author(s):

Ming Han ◽

Han Liu

Keyword(s):

Deep Learning ◽

Resolution Enhancement ◽

Super Resolution ◽

Single Image ◽

Image Super Resolution ◽

Single Image Super Resolution ◽

Enhancement Algorithm

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Video Super Resolution Using Duality Based TV-L 1 Optical Flow

Lecture Notes in Computer Science - Pattern Recognition ◽

10.1007/978-3-642-03798-6_44 ◽

2009 ◽

pp. 432-441 ◽

Author(s):

Dennis Mitzel ◽

Thomas Pock ◽

Thomas Schoenemann ◽

Daniel Cremers

Keyword(s):

Optical Flow ◽

Super Resolution

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OPTICAL FLOW ESTIMATION WITH CONFIDENCE MEASURES FOR SUPER-RESOLUTION BASED ON RECURSIVE ROBUST TOTAL LEAST SQUARES

Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods ◽

10.5220/0003785904630469 ◽

2012 ◽

Keyword(s):

Optical Flow ◽

Least Squares ◽

Super Resolution ◽

Total Least Squares ◽

Confidence Measures ◽

Flow Estimation ◽

Optical Flow Estimation

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Low dose 4D-CT super-resolution reconstruction via inter-plane motion estimation based on optical flow

Biomedical Signal Processing and Control ◽

10.1016/j.bspc.2020.102085 ◽

2020 ◽

Vol 62 ◽

pp. 102085

Author(s):

Hui Liu ◽

Yuxiu Lin ◽

Bulat Ibragimov ◽

Caiming Zhang

Keyword(s):

Motion Estimation ◽

Optical Flow ◽

Low Dose ◽

Super Resolution ◽

Plane Motion ◽

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Image super resolution with adaptive edge enhancement algorithm

10.1117/12.2050038 ◽

2014 ◽

Author(s):

Jaturon Ngernplubpla ◽

Orachat Chitsobhuk

Keyword(s):

Super Resolution ◽

Edge Enhancement ◽

Image Super Resolution ◽

Enhancement Algorithm

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Is Super-Resolution with Optical Flow Feasible?

Computer Vision — ECCV 2002 - Lecture Notes in Computer Science ◽

10.1007/3-540-47969-4_40 ◽

2002 ◽

pp. 599-613 ◽

Author(s):

WenYi Zhao ◽

Harpreet S. Sawhney

Keyword(s):

Optical Flow ◽

Super Resolution

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A Robust Video Super-Resolution Using a Recursive Leclerc Bayesian Approach with an OFOM (Optical Flow Observation Model)

2012 26th International Conference on Advanced Information Networking and Applications Workshops ◽

10.1109/waina.2012.63 ◽

2012 ◽

Author(s):

Parinya Sanguansat ◽

Kornkamol Thakulsukanant ◽

Vorapoj Patanavijit

Keyword(s):

Optical Flow ◽

Bayesian Approach ◽

Super Resolution ◽

Observation Model

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