On the nonparametric impulsive noise reduction in multichannel images

Bogdan Smolka

doi:10.1007/978-3-540-44871-6_113

On the nonparametric impulsive noise reduction in multichannel images

Bogdan Smolka

Department of Data Science and Engineering (RAU/RAU4)

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

This paper presents a new filtering scheme for the removal of impulsive noise in multichannel images. It is based on estimating the probability density function for image pixels in a filtering window by means of the kernel density estimation method. The filtering algorithm itself is based on the comparison of pixels with their neighborhood in a sliding filter window. The quality of noise suppression and detail preservation of the new filter is measured quantitatively in terms of the standard image quality criteria. The filtering results obtained with the new filter show its excellent ability to reduce noise while simultaneously preserving fine image details.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Francisco Jose Perales, Aurelio J. C. Campilho, Nicolas Perez Perez, Nicolas Perez Perez
Publisher	Springer Verlag
Pages	979-985
Number of pages	7
ISBN (Print)	3540402179, 9783540402176
DOIs	https://doi.org/10.1007/978-3-540-44871-6_113
Publication status	Published - 2003

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2652
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-44871-6_113

Cite this

Smolka, B. (2003). On the nonparametric impulsive noise reduction in multichannel images. In F. J. Perales, A. J. C. Campilho, N. P. Perez, & N. P. Perez (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 979-985). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2652). Springer Verlag. https://doi.org/10.1007/978-3-540-44871-6_113

Smolka, Bogdan. / On the nonparametric impulsive noise reduction in multichannel images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Francisco Jose Perales ; Aurelio J. C. Campilho ; Nicolas Perez Perez ; Nicolas Perez Perez. Springer Verlag, 2003. pp. 979-985 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inbook{bfcc3037fe5746fc8c2be36926fb9666,

title = "On the nonparametric impulsive noise reduction in multichannel images",

abstract = "This paper presents a new filtering scheme for the removal of impulsive noise in multichannel images. It is based on estimating the probability density function for image pixels in a filtering window by means of the kernel density estimation method. The filtering algorithm itself is based on the comparison of pixels with their neighborhood in a sliding filter window. The quality of noise suppression and detail preservation of the new filter is measured quantitatively in terms of the standard image quality criteria. The filtering results obtained with the new filter show its excellent ability to reduce noise while simultaneously preserving fine image details.",

author = "Bogdan Smolka",

year = "2003",

doi = "10.1007/978-3-540-44871-6\_113",

language = "English",

isbn = "3540402179",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "979--985",

editor = "Perales, \{Francisco Jose\} and Campilho, \{Aurelio J. C.\} and Perez, \{Nicolas Perez\} and Perez, \{Nicolas Perez\}",

booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

address = "Germany",

}

Smolka, B 2003, On the nonparametric impulsive noise reduction in multichannel images. in FJ Perales, AJC Campilho, NP Perez & NP Perez (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2652, Springer Verlag, pp. 979-985. https://doi.org/10.1007/978-3-540-44871-6_113

On the nonparametric impulsive noise reduction in multichannel images. / Smolka, Bogdan.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Francisco Jose Perales; Aurelio J. C. Campilho; Nicolas Perez Perez; Nicolas Perez Perez. Springer Verlag, 2003. p. 979-985 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2652).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - On the nonparametric impulsive noise reduction in multichannel images

AU - Smolka, Bogdan

PY - 2003

Y1 - 2003

N2 - This paper presents a new filtering scheme for the removal of impulsive noise in multichannel images. It is based on estimating the probability density function for image pixels in a filtering window by means of the kernel density estimation method. The filtering algorithm itself is based on the comparison of pixels with their neighborhood in a sliding filter window. The quality of noise suppression and detail preservation of the new filter is measured quantitatively in terms of the standard image quality criteria. The filtering results obtained with the new filter show its excellent ability to reduce noise while simultaneously preserving fine image details.

AB - This paper presents a new filtering scheme for the removal of impulsive noise in multichannel images. It is based on estimating the probability density function for image pixels in a filtering window by means of the kernel density estimation method. The filtering algorithm itself is based on the comparison of pixels with their neighborhood in a sliding filter window. The quality of noise suppression and detail preservation of the new filter is measured quantitatively in terms of the standard image quality criteria. The filtering results obtained with the new filter show its excellent ability to reduce noise while simultaneously preserving fine image details.

UR - https://www.scopus.com/pages/publications/35248888622

U2 - 10.1007/978-3-540-44871-6_113

DO - 10.1007/978-3-540-44871-6_113

M3 - Chapter

AN - SCOPUS:35248888622

SN - 3540402179

SN - 9783540402176

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 979

EP - 985

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

A2 - Perales, Francisco Jose

A2 - Campilho, Aurelio J. C.

A2 - Perez, Nicolas Perez

PB - Springer Verlag

ER -

Smolka B. On the nonparametric impulsive noise reduction in multichannel images. In Perales FJ, Campilho AJC, Perez NP, Perez NP, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2003. p. 979-985. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-44871-6_113

On the nonparametric impulsive noise reduction in multichannel images

Abstract

Publication series

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this