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Séminaire du jeudi 15/10/2015

Date: 
Jeudi, Octobre 15, 2015 - 14:00
localisation: 
Laboratoire IMS

Orateur : Jérôme Idier

Affiliation : Equipe ADTSI, IRCCyN, Nantes

Titre : Etude théorique de la capacité de super-résolution en microscopie de fluorescence à éclairement de type speckle

Résumé : A préciser

Orateur : Marco Bevilacqua

Affiliation : Labri/IMB

Title: Example-based algorithms for single-image super-resolution

Abstract : Super-resolution (SR) refers to a family of methods that aim at increasing the resolution of given images to a greater extent than traditional image processing techniques. In particular, example-based SR methods typically employ tools from the machine learning field, to estimate patch-by-patch the high-resolution (HR) version of a single low-resolution (LR) input image. In order to perform this task, they make use of a dictionary of "examples" (pairs of LR/HR patches), which can either be trained from external images (leading to an external dictionary), or derived by looking for self-similarities within the input image itself (we then have an "internal" dictionary).
In this talk, after providing some context, I will describe two distinct example-based SR algorithms, one for each kind of dictionary, developed as part of my PhD thesis work.