A simple fuzzy method to remove mixed Gaussian-Impulsive noise from color images

Mixed impulsive and Gaussian noise reduction from digital color images is a challenging task because it is necessary to appropriately process both types of noise that in turn need to be distinguished from the original image structures such as edges and details. Fuzzy theory is useful to build simple...

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Detalles Bibliográficos
Autores: Camarena Estruch, Joan Gerard, Gregori Gregori, Valentín|||0000-0002-5983-6182, Morillas, Samuel|||0000-0001-9262-6139, Sapena Piera, Almanzor|||0000-0001-8473-6063
Tipo de recurso: artículo
Fecha de publicación:2013
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/38128
Acceso en línea:https://riunet.upv.es/handle/10251/38128
Access Level:acceso abierto
Palabra clave:Color Image Filter
Fuzzy Metrics
Fuzzy Rule
Vector Median Filter
LENGUAJES Y SISTEMAS INFORMATICOS
MATEMATICA APLICADA
Descripción
Sumario:Mixed impulsive and Gaussian noise reduction from digital color images is a challenging task because it is necessary to appropriately process both types of noise that in turn need to be distinguished from the original image structures such as edges and details. Fuzzy theory is useful to build simple, efficient, and effective solutions for this problem. In this paper, we propose a fuzzy method to reduce Gaussian and impulsive noise from color images. Our method uses one only filtering operation: a weighted averaging. A fuzzy rule system is used to assign the weights in the averaging so that both noise types are reduced and image structures are reserved. We provide experimental results to show that the performance of the method is competitive with respect to state-of-the-art filters.