Joint Super-Resolution and segmentation from a set of Low Resolution images using a Bayesian approach with a Gauss-Markov-Potts Prior

Majdi Mansouri; Ali Mohammad-Djafari

doi:10.1504/IJSISE.2010.038017

Journal articles

Joint Super-Resolution and segmentation from a set of Low Resolution images using a Bayesian approach with a Gauss-Markov-Potts Prior

Majdi Mansouri ¹ Ali Mohammad-Djafari ²

1 LM2S - Laboratoire Modélisation et Sûreté des Systèmes

ICD - Institut Charles Delaunay

2 L2S - Laboratoire des signaux et systèmes

Mots-clés : super-resolution

Document type :

Journal articles

Domain :

Engineering Sciences [physics] / Signal and Image processing

Computer Science [cs] / Signal and Image Processing

Complete list of metadata

https://hal-supelec.archives-ouvertes.fr/hal-00658306
Contributor : Ali Mohammad-Djafari <>
Submitted on : Tuesday, January 10, 2012 - 11:31:02 AM
Last modification on : Thursday, June 17, 2021 - 3:47:37 AM

Joint Super-Resolution and segmentation from a set of Low Resolution images using a Bayesian approach with a Gauss-Markov-Potts Prior

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Joint Super-Resolution and segmentation from a set of Low Resolution images using a Bayesian approach with a Gauss-Markov-Potts Prior

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