Automatic estimation of the noise level function for adaptive blind denoising - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2016

Automatic estimation of the noise level function for adaptive blind denoising

Résumé

Image denoising is a fundamental problem in image processing and many powerful algorithms have been developed. However, they often rely on the knowledge of the noise distribution and its parameters. We propose a fully blind denoising method that first estimates the noise level function then uses this estimation for automatic denoising. First we perform the non-parametric detection of homogeneous image regions in order to compute a scatterplot of the noise statistics, then we estimate the noise level function with the least absolute deviation estimator. The noise level function parameters are then directly re-injected into an adaptive denoising algorithm based on the non-local means with no prior model fitting. Results show the performance of the noise estimation and denoising methods, and we provide a robust blind denoising tool.
Fichier principal
Vignette du fichier
PID4304835.pdf (2.04 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01450723 , version 1 (31-01-2017)

Identifiants

Citer

Camille Sutour, Jean-François Aujol, Charles-Alban Deledalle. Automatic estimation of the noise level function for adaptive blind denoising. 24th European Signal Processing Conference (EUSIPCO), 2016, Aug 2016, Budapest, Hungary. pp.76 - 80, ⟨10.1109/EUSIPCO.2016.7760213⟩. ⟨hal-01450723⟩

Collections

CNRS IMB
428 Consultations
620 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More