dc.creatorForero, Manuel G.
dc.creatorMiranda, Sergio L.
dc.creatorJacanamejoy-Jamioy, Carlos
dc.date2020-09-16T15:01:31Z
dc.date2020-09-16T15:01:31Z
dc.date2020-06-24
dc.date.accessioned2023-08-31T19:04:10Z
dc.date.available2023-08-31T19:04:10Z
dc.identifierForero, M.G., Miranda, S.L., & Jacanamejoy-Jamioy, C.A. (2020). Improvement of the Turajli? Method for the Estimation of Gaussian Noise in Images. Pattern Recognition, 12088, 108 - 117.
dc.identifier0302-9743
dc.identifierhttps://link.springer.com/chapter/10.1007/978-3-030-49076-8_11
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8555168
dc.descriptionGaussian noise estimation is an important step in some of the more recently developed noise removal methods. This is a difficult task and although several estimation techniques have been proposed recently, they generally do not produce good results. In a previous comparative study, among several noise estimation techniques, a method proposed in 2017 by Turajli? was found to give the best results. Although acceptable, they are still far from ideal. Therefore, several changes to this method are introduced in this paper to improve the estimation. Tests on monochromatic images contaminated with different levels of Gaussian noise showed that the modified method produces a significant improvement in the estimation of Gaussian noise, over 35%, at a slightly higher computational cost.
dc.descriptionUniversidad de Ibagu?
dc.languageen
dc.publisherLecture notes in computer sciences
dc.subjectNoise estimation
dc.subjectGaussian noise
dc.subjectImage filtering
dc.subjectSmoothing filters
dc.subjectNoise reduction
dc.titleImprovement of the Turajli? Method for the Estimation of Gaussian Noise in Images
dc.typeArticle


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