An efficient nonlinear approach for removing fixed-value impulse noise from grayscale images

Dante Mújica-Vargas, José de Jesús Rubio, Jean Marie Vianney Kinani, Francisco J. Gallegos-Funes

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

© 2017, Springer-Verlag GmbH Germany, part of Springer Nature. Removal of salt and pepper noise has been one of the most interesting researches in the field of image preprocessing tasks; it has two simultaneous stringent demands: the suppression of impulses and the preservation of fine details. To address this problem, a scheme based on nonlinear filters is proposed; it consists of the introduction of a redescending M-estimator within the modified nearest neighbor filter. In order to analyze all pixels in the neighborhood, as well as to reduce the magnitude of the existing impulses, a redescending M-estimator is used; the remaining pixels are processed by the modified nearest neighbor filter to obtain the best estimation of a noise-free pixel. The impulsive suppression is applied on the entire image by using a sliding window; the local information obtained by this one also allows to calculate the thresholds that characterize the influence function tested in the redescending M-estimator. To suppress high density fixed-value impulse noise in large-size grayscale images, the proposal is implemented on a heterogeneous CPU–GPU architecture. The noise reduction and the processing time of the proposed approach are evaluated by extensive simulations; its effectiveness is verified by quantitative and qualitative results.
Original languageAmerican English
Pages617-633
Number of pages553
DOIs
StatePublished - 1 Mar 2018
EventJournal of Real-Time Image Processing -
Duration: 1 Mar 2018 → …

Conference

ConferenceJournal of Real-Time Image Processing
Period1/03/18 → …

Fingerprint

Noise
Germany
Salts
Research

Cite this

Mújica-Vargas, Dante ; de Jesús Rubio, José ; Kinani, Jean Marie Vianney ; Gallegos-Funes, Francisco J. / An efficient nonlinear approach for removing fixed-value impulse noise from grayscale images. Paper presented at Journal of Real-Time Image Processing, .553 p.
@conference{628ee153cb794deebd3a5d62e9467592,
title = "An efficient nonlinear approach for removing fixed-value impulse noise from grayscale images",
abstract = "{\circledC} 2017, Springer-Verlag GmbH Germany, part of Springer Nature. Removal of salt and pepper noise has been one of the most interesting researches in the field of image preprocessing tasks; it has two simultaneous stringent demands: the suppression of impulses and the preservation of fine details. To address this problem, a scheme based on nonlinear filters is proposed; it consists of the introduction of a redescending M-estimator within the modified nearest neighbor filter. In order to analyze all pixels in the neighborhood, as well as to reduce the magnitude of the existing impulses, a redescending M-estimator is used; the remaining pixels are processed by the modified nearest neighbor filter to obtain the best estimation of a noise-free pixel. The impulsive suppression is applied on the entire image by using a sliding window; the local information obtained by this one also allows to calculate the thresholds that characterize the influence function tested in the redescending M-estimator. To suppress high density fixed-value impulse noise in large-size grayscale images, the proposal is implemented on a heterogeneous CPU–GPU architecture. The noise reduction and the processing time of the proposed approach are evaluated by extensive simulations; its effectiveness is verified by quantitative and qualitative results.",
author = "Dante M{\'u}jica-Vargas and {de Jes{\'u}s Rubio}, Jos{\'e} and Kinani, {Jean Marie Vianney} and Gallegos-Funes, {Francisco J.}",
year = "2018",
month = "3",
day = "1",
doi = "10.1007/s11554-017-0746-8",
language = "American English",
pages = "617--633",
note = "Journal of Real-Time Image Processing ; Conference date: 01-03-2018",

}

Mújica-Vargas, D, de Jesús Rubio, J, Kinani, JMV & Gallegos-Funes, FJ 2018, 'An efficient nonlinear approach for removing fixed-value impulse noise from grayscale images', Paper presented at Journal of Real-Time Image Processing, 1/03/18 pp. 617-633. https://doi.org/10.1007/s11554-017-0746-8

An efficient nonlinear approach for removing fixed-value impulse noise from grayscale images. / Mújica-Vargas, Dante; de Jesús Rubio, José; Kinani, Jean Marie Vianney; Gallegos-Funes, Francisco J.

2018. 617-633 Paper presented at Journal of Real-Time Image Processing, .

Research output: Contribution to conferencePaper

TY - CONF

T1 - An efficient nonlinear approach for removing fixed-value impulse noise from grayscale images

AU - Mújica-Vargas, Dante

AU - de Jesús Rubio, José

AU - Kinani, Jean Marie Vianney

AU - Gallegos-Funes, Francisco J.

PY - 2018/3/1

Y1 - 2018/3/1

N2 - © 2017, Springer-Verlag GmbH Germany, part of Springer Nature. Removal of salt and pepper noise has been one of the most interesting researches in the field of image preprocessing tasks; it has two simultaneous stringent demands: the suppression of impulses and the preservation of fine details. To address this problem, a scheme based on nonlinear filters is proposed; it consists of the introduction of a redescending M-estimator within the modified nearest neighbor filter. In order to analyze all pixels in the neighborhood, as well as to reduce the magnitude of the existing impulses, a redescending M-estimator is used; the remaining pixels are processed by the modified nearest neighbor filter to obtain the best estimation of a noise-free pixel. The impulsive suppression is applied on the entire image by using a sliding window; the local information obtained by this one also allows to calculate the thresholds that characterize the influence function tested in the redescending M-estimator. To suppress high density fixed-value impulse noise in large-size grayscale images, the proposal is implemented on a heterogeneous CPU–GPU architecture. The noise reduction and the processing time of the proposed approach are evaluated by extensive simulations; its effectiveness is verified by quantitative and qualitative results.

AB - © 2017, Springer-Verlag GmbH Germany, part of Springer Nature. Removal of salt and pepper noise has been one of the most interesting researches in the field of image preprocessing tasks; it has two simultaneous stringent demands: the suppression of impulses and the preservation of fine details. To address this problem, a scheme based on nonlinear filters is proposed; it consists of the introduction of a redescending M-estimator within the modified nearest neighbor filter. In order to analyze all pixels in the neighborhood, as well as to reduce the magnitude of the existing impulses, a redescending M-estimator is used; the remaining pixels are processed by the modified nearest neighbor filter to obtain the best estimation of a noise-free pixel. The impulsive suppression is applied on the entire image by using a sliding window; the local information obtained by this one also allows to calculate the thresholds that characterize the influence function tested in the redescending M-estimator. To suppress high density fixed-value impulse noise in large-size grayscale images, the proposal is implemented on a heterogeneous CPU–GPU architecture. The noise reduction and the processing time of the proposed approach are evaluated by extensive simulations; its effectiveness is verified by quantitative and qualitative results.

UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85039695681&origin=inward

UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85039695681&origin=inward

U2 - 10.1007/s11554-017-0746-8

DO - 10.1007/s11554-017-0746-8

M3 - Paper

SP - 617

EP - 633

ER -