Nonlinear image processing and filtering: A unified approach based on vertically weighted regression - Rafajłowicz, Ewaryst (1953- ); Pawlak, Mirosław; Steland, Angsar (Zielona Góra: Uniwersytet Zielonogórski)
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.
Keywords: image filtering; vertically weighted regression; nonlinear filters