Removal of impulse noise using gain factors adapted by noise-free pixel number and pixel variation

Ching Ta Lu; Jun Hong Shen; Mu Yen Chen; Ling Ling Wang; Chih Chan Hsu

doi:10.1007/978-981-10-7398-4_1

Removal of impulse noise using gain factors adapted by noise-free pixel number and pixel variation

Ching Ta Lu, Jun Hong Shen, Mu Yen Chen, Ling Ling Wang, Chih Chan Hsu

Department of Engineering Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Impulse noise impacts an image, causing the quality of image to be deteriorated in image transmission or capture. In this paper, we propose a gain factor for the removal of the impulse noise. A 3 × 3 fixed-size local window is employed to analyze each extreme pixel (0 or 255 for an 8-bit gray-level image). All non-extreme pixels are sorted in an ascending order and are grouped according to the variation of pixel levels. If the pixel level between adjacent two sorted pixels varies seriously, a new group is created. Hence, the ratio and median value of each group are computed to determine the values of the gain factors. They are multiplied with the median value of each group to obtain the weighted value which is employed to replace the center pixel with an extreme value, enabling noise-corrupted pixels to be restored. Experimental results show that the proposed method can effectively remove salt-and-pepper noise from a corrupted image for various noise corruption densities (from 10% to 90%); meanwhile, the denoised image is freed from the blurred effect.

Original language	English
Title of host publication	Frontier Computing - Theory, Technologies and Applications FC 2017
Editors	Neil Y. Yen, Jason C. Hung, Lin Hui
Publisher	Springer Verlag
Pages	1-11
Number of pages	11
ISBN (Print)	9789811073977
DOIs	https://doi.org/10.1007/978-981-10-7398-4_1
Publication status	Published - 2018
Event	6th International Conference on Frontier Computing, FC 2017 - Osaka, Japan Duration: 2017 Jul 12 → 2017 Jul 14

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	464
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	6th International Conference on Frontier Computing, FC 2017
Country/Territory	Japan
City	Osaka
Period	17-07-12 → 17-07-14

All Science Journal Classification (ASJC) codes

Industrial and Manufacturing Engineering

Access to Document

10.1007/978-981-10-7398-4_1

Cite this

Lu, C. T., Shen, J. H., Chen, M. Y., Wang, L. L., & Hsu, C. C. (2018). Removal of impulse noise using gain factors adapted by noise-free pixel number and pixel variation. In N. Y. Yen, J. C. Hung, & L. Hui (Eds.), Frontier Computing - Theory, Technologies and Applications FC 2017 (pp. 1-11). (Lecture Notes in Electrical Engineering; Vol. 464). Springer Verlag. https://doi.org/10.1007/978-981-10-7398-4_1

@inproceedings{2d287544202e41d49f658513b61de426,

title = "Removal of impulse noise using gain factors adapted by noise-free pixel number and pixel variation",

abstract = "Impulse noise impacts an image, causing the quality of image to be deteriorated in image transmission or capture. In this paper, we propose a gain factor for the removal of the impulse noise. A 3 × 3 fixed-size local window is employed to analyze each extreme pixel (0 or 255 for an 8-bit gray-level image). All non-extreme pixels are sorted in an ascending order and are grouped according to the variation of pixel levels. If the pixel level between adjacent two sorted pixels varies seriously, a new group is created. Hence, the ratio and median value of each group are computed to determine the values of the gain factors. They are multiplied with the median value of each group to obtain the weighted value which is employed to replace the center pixel with an extreme value, enabling noise-corrupted pixels to be restored. Experimental results show that the proposed method can effectively remove salt-and-pepper noise from a corrupted image for various noise corruption densities (from 10% to 90%); meanwhile, the denoised image is freed from the blurred effect.",

author = "Lu, {Ching Ta} and Shen, {Jun Hong} and Chen, {Mu Yen} and Wang, {Ling Ling} and Hsu, {Chih Chan}",

note = "Funding Information: Acknowledgments. This research was supported by the Ministry of Science and Technology, Taiwan, under contract numbers MOST 105-2410-H-468-012 and MOST 104-2221-E-468-007. Publisher Copyright: {\textcopyright} 2018, Springer Nature Singapore Pte Ltd.; 6th International Conference on Frontier Computing, FC 2017 ; Conference date: 12-07-2017 Through 14-07-2017",

year = "2018",

doi = "10.1007/978-981-10-7398-4_1",

language = "English",

isbn = "9789811073977",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Verlag",

pages = "1--11",

editor = "Yen, {Neil Y.} and Hung, {Jason C.} and Lin Hui",

booktitle = "Frontier Computing - Theory, Technologies and Applications FC 2017",

address = "Germany",

}

Lu, CT, Shen, JH, Chen, MY, Wang, LL & Hsu, CC 2018, Removal of impulse noise using gain factors adapted by noise-free pixel number and pixel variation. in NY Yen, JC Hung & L Hui (eds), Frontier Computing - Theory, Technologies and Applications FC 2017. Lecture Notes in Electrical Engineering, vol. 464, Springer Verlag, pp. 1-11, 6th International Conference on Frontier Computing, FC 2017, Osaka, Japan, 17-07-12. https://doi.org/10.1007/978-981-10-7398-4_1

Removal of impulse noise using gain factors adapted by noise-free pixel number and pixel variation. / Lu, Ching Ta; Shen, Jun Hong; Chen, Mu Yen et al.
Frontier Computing - Theory, Technologies and Applications FC 2017. ed. / Neil Y. Yen; Jason C. Hung; Lin Hui. Springer Verlag, 2018. p. 1-11 (Lecture Notes in Electrical Engineering; Vol. 464).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Lu, Ching Ta

AU - Shen, Jun Hong

AU - Chen, Mu Yen

AU - Wang, Ling Ling

AU - Hsu, Chih Chan

N1 - Funding Information: Acknowledgments. This research was supported by the Ministry of Science and Technology, Taiwan, under contract numbers MOST 105-2410-H-468-012 and MOST 104-2221-E-468-007. Publisher Copyright: © 2018, Springer Nature Singapore Pte Ltd.

PY - 2018

Y1 - 2018

N2 - Impulse noise impacts an image, causing the quality of image to be deteriorated in image transmission or capture. In this paper, we propose a gain factor for the removal of the impulse noise. A 3 × 3 fixed-size local window is employed to analyze each extreme pixel (0 or 255 for an 8-bit gray-level image). All non-extreme pixels are sorted in an ascending order and are grouped according to the variation of pixel levels. If the pixel level between adjacent two sorted pixels varies seriously, a new group is created. Hence, the ratio and median value of each group are computed to determine the values of the gain factors. They are multiplied with the median value of each group to obtain the weighted value which is employed to replace the center pixel with an extreme value, enabling noise-corrupted pixels to be restored. Experimental results show that the proposed method can effectively remove salt-and-pepper noise from a corrupted image for various noise corruption densities (from 10% to 90%); meanwhile, the denoised image is freed from the blurred effect.

AB - Impulse noise impacts an image, causing the quality of image to be deteriorated in image transmission or capture. In this paper, we propose a gain factor for the removal of the impulse noise. A 3 × 3 fixed-size local window is employed to analyze each extreme pixel (0 or 255 for an 8-bit gray-level image). All non-extreme pixels are sorted in an ascending order and are grouped according to the variation of pixel levels. If the pixel level between adjacent two sorted pixels varies seriously, a new group is created. Hence, the ratio and median value of each group are computed to determine the values of the gain factors. They are multiplied with the median value of each group to obtain the weighted value which is employed to replace the center pixel with an extreme value, enabling noise-corrupted pixels to be restored. Experimental results show that the proposed method can effectively remove salt-and-pepper noise from a corrupted image for various noise corruption densities (from 10% to 90%); meanwhile, the denoised image is freed from the blurred effect.

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BT - Frontier Computing - Theory, Technologies and Applications FC 2017

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Removal of impulse noise using gain factors adapted by noise-free pixel number and pixel variation

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