loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: X. Descombes 1 ; M. Lebellego 2 and E. Zhizhina 3

Affiliations: 1 Ariana Research Group, France ; 2 Ariana Research Group; Dobrushin Laboratory, Russian Federation ; 3 Dobrushin Laboratory, Russian Federation

Keyword(s): Image deconvolution, Stochastic Differential Equation, Langevin dynamics, Euler approximation.

Abstract: We consider the problem of image deconvolution. We foccus on a Bayesian approach which consists of maximizing an energy obtained by a Markov Random Field modeling. MRFs are classically optimized by a MCMC sampler embeded into a simulated annealing scheme. In a previous work, we have shown that, in the context of image denoising, a diffusion process can outperform the MCMC approach in term of computational time. Herein, we extend this approach to the case of deconvolution. We first study the case where the kernel is known. Then, we address the myopic and blind deconvolutions.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.224.55.193

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Descombes, X.; Lebellego, M. and Zhizhina, E. (2007). IMAGE DECONVOLUTION USING A STOCHASTIC DIFFERENTIAL EQUATION APPROACH. In Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISAPP 2007) - Bayesian Approach for Inverse Problems in Computer Vision; ISBN 978-972-8865-75-7; ISSN 2184-4321, SciTePress, pages 157-164. DOI: 10.5220/0002064701570164

@conference{bayesian approach for inverse problems in computer vision07,
author={X. Descombes. and M. Lebellego. and E. Zhizhina.},
title={IMAGE DECONVOLUTION USING A STOCHASTIC DIFFERENTIAL EQUATION APPROACH},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISAPP 2007) - Bayesian Approach for Inverse Problems in Computer Vision},
year={2007},
pages={157-164},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002064701570164},
isbn={978-972-8865-75-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISAPP 2007) - Bayesian Approach for Inverse Problems in Computer Vision
TI - IMAGE DECONVOLUTION USING A STOCHASTIC DIFFERENTIAL EQUATION APPROACH
SN - 978-972-8865-75-7
IS - 2184-4321
AU - Descombes, X.
AU - Lebellego, M.
AU - Zhizhina, E.
PY - 2007
SP - 157
EP - 164
DO - 10.5220/0002064701570164
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic