@misc{Rafajłowicz_Ewaryst_Nonlinear,
 author={Rafajłowicz, Ewaryst and Pawlak, Mirosław and Steland, Angsar},
 howpublished={online},
 publisher={Zielona Góra: Uniwersytet Zielonogórski},
 language={eng},
 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.},
 type={artykuł},
 title={Nonlinear image processing and filtering: A unified approach based on vertically weighted regression},
 keywords={image filtering, vertically weighted regression, nonlinear filters},
}