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Nonlinear image processing and filtering: A unified approach based on vertically weighted regression

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Title: Nonlinear image processing and filtering: A unified approach based on vertically weighted regression

Creator:

Rafajłowicz, Ewaryst (1953- ) ; Pawlak, Mirosław ; Steland, Angsar

Date:

2008

Resource Type:

artykuł

Contributor:

Kummert, Anton - ed. ; Rafajłowicz, Ewaryst - ed.

Subtitle:

.

Group publication title:

AMCS, volume 18 (2008)

Abstract:

A class of nonparametric smoothing kernel methods for image processing and filtering that possess edge-preserving properties is examined. The proposed approach is a nonlinearly modified version of the classical nonparametric regression estimates utilizing the concept of vertical weighting. The method unifies a number of known nonlinear image filtering and denoising algorithms such as bilateral and steering kernel filters. It is shown that vertically weighted filters can be realized by a structure of three interconnected radial basis function (RBF) networks. We also assess the performance of the algorithm by studying industrial images.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Resource Identifier:

oai:zbc.uz.zgora.pl:78696

DOI:

10.2478/v10006-008-0005-z

Pages:

49-61

Source:

AMCS, volume 18, number 1 (2008) ; click here to follow the link

Language:

eng

Rights:

Biblioteka Uniwersytetu Zielonogórskiego

Subject and keywords:

image filtering vertically weighted regression nonlinear filters

Object collections:

Last modified:

Nov 8, 2024

In our library since:

Apr 4, 2024

Number of object content hits:

35

All available object's versions:

https://zbc.uz.zgora.pl/repozytorium/publication/88440

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Edition name Date
Nonlinear image processing and filtering: A unified approach based on vertically weighted regression Nov 8, 2024

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