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A two-stage filter for removing salt-and-pepper noise using noise detector based on characteristic difference parameter and adaptive directional mean filter.
Ma, Hongjin; Nie, Yufeng.
Afiliação
  • Ma H; School of Science, Northwestern Polytechnical University, Xi'an, 710129, China.
  • Nie Y; School of Science, Northwestern Polytechnical University, Xi'an, 710129, China.
PLoS One ; 13(10): e0205736, 2018.
Article em En | MEDLINE | ID: mdl-30365501
In this paper, a two-stage filter for removing salt-and-pepper noise using noise detector based on characteristic difference parameter and adaptive directional mean filter is proposed. The first stage firstly detects the noise corrupted pixels by combining characteristic difference parameter and gray level extreme, then develops an improved adaptive median filter to firstly restore them. The second stage introduces a restoration scheme to further restore the noise corrupted pixels, which firstly divides them into two types and then applies different restoration skills for the pixels based on the classification result. One type of pixels is restored by the mean filter and the other type of pixels is restored by the proposed adaptive directional mean filter. The new filter firstly adaptively selects the optimal filtering window and direction template, then replaces the gray level of noise corrupted pixel by the mean value of pixels on the optimal template. Experimental results show that the proposed filter outperforms many existing main filters in terms of noise suppression and detail preservation.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Interpretação de Imagem Assistida por Computador / Aumento da Imagem Tipo de estudo: Evaluation_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Interpretação de Imagem Assistida por Computador / Aumento da Imagem Tipo de estudo: Evaluation_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article