TY - JOUR
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.
N1 - Publisher Copyright:
© 2017, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2018/3/1
Y1 - 2018/3/1
N2 - 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 - 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.
KW - GPU
KW - Grayscale images
KW - Noise suppression
KW - Nonlinear approach
KW - Salt and pepper noise
UR - http://www.scopus.com/inward/record.url?scp=85039695681&partnerID=8YFLogxK
U2 - 10.1007/s11554-017-0746-8
DO - 10.1007/s11554-017-0746-8
M3 - Artículo
AN - SCOPUS:85039695681
SN - 1861-8200
VL - 14
SP - 617
EP - 633
JO - Journal of Real-Time Image Processing
JF - Journal of Real-Time Image Processing
IS - 3
ER -