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Impulse Noise Cancellation of Medical Images Using Wavelet Networks and Median Filters

This paper presents a new two-stage approach to impulse noise removal for medical images based on wavelet network (WN). The first step is noise detection, in which the so-called gray-level difference and average background difference are considered as the inputs of a WN. Wavelet Network is used as a...

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Detalles Bibliográficos
Autores principales: Sadri, Amir Reza, Zekri, Maryam, Sadri, Saeid, Gheissari, Niloofar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3592502/
https://www.ncbi.nlm.nih.gov/pubmed/23493998
Descripción
Sumario:This paper presents a new two-stage approach to impulse noise removal for medical images based on wavelet network (WN). The first step is noise detection, in which the so-called gray-level difference and average background difference are considered as the inputs of a WN. Wavelet Network is used as a preprocessing for the second stage. The second step is removing impulse noise with a median filter. The wavelet network presented here is a fixed one without learning. Experimental results show that our method acts on impulse noise effectively, and at the same time preserves chromaticity and image details very well.