BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:On the use of Gaussian models on patches for image denoising - Ant
 oine Houdard\, Institut de Mathématiques de Bordeaux
DTSTART:20190321T110000Z
DTEND:20190321T120000Z
UID:TALK121591@talks.cam.ac.uk
CONTACT:AI Aviles-Rivero
DESCRIPTION:Some recent denoising methods are based on a statistical model
 ing of the image patches. In the literature\, Gaussian models or Gaussian 
 mixture models are the most widely used priors.\nIn this presentation\, af
 ter introducing the statistical framework of patch-based image denoising\,
  I will propose some clues to answer the following questions: Why are thes
 e Gaussian priors so widely used? What information do they encode? In the 
 second part\, I will present a mixture model for noisy patches adapted to 
 the high dimension of the patch space. This results in a denoising algorit
 hm only based on statistical tools\, which achieves state-of-the-art perfo
 rmance. Finally\, I will discuss the limitations and some developments of 
 the proposed method.
LOCATION:MR15\,  Centre for Mathematical Sciences\, Wilberforce Road\, Cam
 bridge
END:VEVENT
END:VCALENDAR