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

• Autorzy: Rafajłowicz E. , Pawlak M. , Steland A.
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

image filtering; vertically weighted regression; nonlinear filters

PL

filtr nieliniowy; filtracja obrazu; regresja ważona

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2008
• Tom: Vol. 18, no 1
• Strony: 49--61
• Opis fizyczny: Bibliogr. 26 poz., rys.

Twórcy

autor

Rafajłowicz E.

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

autor

Pawlak M.

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

autor

Steland A.

• Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Manitoba, R3T5V6, Canada; RWTH Aachen University, Aachen, Germany

Bibliografia

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