<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

Nonlinear Image Processing and Filtering: A Unified Approach Based on Vertically Weighted Regression

Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, ul. Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Manitoba, R3T5V6, Canada

International Journal of Applied Mathematics and Computer Science

A class of nonparametric smoothing kernel methods for image processing and filtering that possess edge-preserving properties is examined. The proposed approach...

Nonlinear Image Processing and Filtering: A Unified Approach Based on Vertically Weighted Regression

Online veröffentlicht: 21. März 2008

Seitenbereich: 49 - 61

DOI: https://doi.org/10.2478/v10006-008-0005-z

Schlüsselwörter
Image filtering, vertically weighted regression, nonlinear filters

This content is open access.

Nonlinear Image Processing and Filtering: A Unified Approach Based on Vertically Weighted Regression

Online veröffentlicht: 21. März 2008

Seitenbereich: 49 - 61

DOI: https://doi.org/10.2478/v10006-008-0005-z

SchlüsselwörterImage filtering, vertically weighted regression, nonlinear filters

This content is open access.

Schlüsselwörter
Image filtering, vertically weighted regression, nonlinear filters