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

2012 ◽  
Author(s):  
Parinya Sanguansat ◽  
Kornkamol Thakulsukanant ◽  
Vorapoj Patanavijit
Keyword(s):  
Optical Flow ◽  
Bayesian Approach ◽  
Super Resolution ◽  
Observation Model

scholarly journals Bayesian analysis of data from segmented super-resolution images for quantifying protein clustering

2020 ◽  
Vol 22 (3) ◽  
pp. 1107-1114
Author(s):  
Tina Košuta ◽  
Marta Cullell-Dalmau ◽  
Francesca Cella Zanacchi ◽  
Carlo Manzo
Keyword(s):  
Bayesian Analysis ◽  
Relative Abundance ◽  
Bayesian Approach ◽  
Super Resolution ◽  
Molecular Aggregates ◽  
Protein Clustering ◽  
Precise Quantification

A Bayesian approach enables the precise quantification of the relative abundance of molecular aggregates of different stoichiometry from segmented super-resolution images.

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

2021 ◽  
Vol 60 (10) ◽  
Author(s):  
Xuan Zhu ◽  
Yuying Jin ◽  
Lin Wang ◽  
Jun Wang ◽  
Zhixiang Lan ◽  
...  
Keyword(s):  
Optical Flow ◽  
Super Resolution ◽  
Flow Compensation

Super-resolution in cardiac MRI using a Bayesian approach

2013 ◽  
Author(s):  
Nelson Velasco Toledo ◽  
Andrea Rueda ◽  
Cristina Santa Marta ◽  
Eduardo Romero
Keyword(s):  
Bayesian Approach ◽  
Cardiac Mri ◽  
Super Resolution

Optical flow based super-resolution: A probabilistic approach

2007 ◽  
Vol 106 (1) ◽  
pp. 106-115 ◽  
Author(s):  
Rik Fransens ◽  
Christoph Strecha ◽  
Luc Van Gool
Keyword(s):  
Optical Flow ◽  
Probabilistic Approach ◽  
Super Resolution

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

2009 ◽  
pp. 432-441 ◽  
Author(s):  
Dennis Mitzel ◽  
Thomas Pock ◽  
Thomas Schoenemann ◽  
Daniel Cremers
Keyword(s):  
Optical Flow ◽  
Super Resolution
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