Variational bayesian super resolution

IEEE Transactions on Image Processing

Volumn 20, Issue 4, 2011, Pages 984-999

  Babacan, S Derin ^a   Molina, Rafael ^b   Katsaggelos, Aggelos K ^c  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b UNIVERSITY OF GRANADA   (Spain)

^c NORTHWESTERN UNIVERSITY   (United States)

Author keywords

Bayesian methods; parameter estimation; super resolution; total variation; variational methods

Indexed keywords

ACCURATE ESTIMATION; ACQUISITION PROCESS; ALGORITHMIC PARAMETERS; BAYESIAN FORMULATION; BAYESIAN METHODS; HIGH RESOLUTION IMAGE; LOW RESOLUTION IMAGES; MODEL PARAMETERS; MOTION PARAMETERS; NOVEL ALGORITHM; PARAMETER-TUNING; PROPAGATION OF ERROR; REGISTRATION ALGORITHMS; STOCHASTIC GENERALIZATIONS; SUB PIXELS; SUPER RESOLUTION; SUPERRESOLUTION METHODS; TOTAL VARIATION; VARIATIONAL BAYESIAN; VARIATIONAL METHODS;

ALGORITHMS; BAYESIAN NETWORKS; ERRORS; MOTION ESTIMATION; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; UNCERTAINTY ANALYSIS;

PARAMETER ESTIMATION;

ALGORITHM; ARTICLE; ARTIFACT; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFACTS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 79952944722     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2010.2080278     Document Type: Article

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