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

Rafajłowicz, E. ; Pawlak, M. ; Steland, A.

International Journal of Applied Mathematics and Computer Science, Tome 18 (2008) no. 1, pp. 49-61.

Résumé

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.

Détail

Keywords: image filtering, vertically weighted regression, nonlinear filters
Mots-clés : filtr nieliniowy, filtracja obrazu, regresja ważona

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