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Estimation of the noise level function based on a non-parametric detection of homogeneous image regions

hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorSUTOUR, Camille
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorDELEDALLE, Charles-Alban
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorAUJOL, Jean-François
dc.date.accessioned2024-04-04T03:11:06Z
dc.date.available2024-04-04T03:11:06Z
dc.date.issued2015-11-17
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193743
dc.description.abstractEnWe propose a two-step algorithm that automatically estimates the noise level function of stationary noise from a single image, i.e., the noise variance as a function of the image intensity. First, the image is divided into small square regions and a non-parametric test is applied to decide weather each region is homogeneous or not. Based on Kendall's τ coefficient (a rank-based measure of correlation), this detector has a non-detection rate independent on the unknown distribution of the noise, provided that it is at least spatially uncorrelated. Moreover, we prove on a toy example, that its overall detection error vanishes with respect to the region size as soon as the signal to noise ratio level is non-zero. Once homogeneous regions are detected, the noise level function is estimated as a second order polynomial minimizing the ℓ 1 error on the statistics of these regions. Numerical experiments show the efficiency of the proposed approach in estimating the noise level function, with a relative error under 10% obtained on a large data set. We illustrate the interest of the approach for an image denoising application.
dc.language.isoen
dc.publisherSociety for Industrial and Applied Mathematics
dc.subject.ennon-parametric detection
dc.subject.ensignal-dependent noise
dc.subject.enNoise level estimation
dc.subject.enleast absolute deviation
dc.title.enEstimation of the noise level function based on a non-parametric detection of homogeneous image regions
dc.typeArticle de revue
dc.identifier.doi10.1137/15M1012682
dc.subject.halInformatique [cs]/Traitement des images
bordeaux.journalSIAM Journal on Imaging Sciences
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01138809
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01138809v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=SIAM%20Journal%20on%20Imaging%20Sciences&rft.date=2015-11-17&rft.au=SUTOUR,%20Camille&DELEDALLE,%20Charles-Alban&AUJOL,%20Jean-Fran%C3%A7ois&rft.genre=article


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