NONLINEAR IMAGE PROCESSING AND FILTERING A UNIFIED APPROACH BASED ON VERTICALLYWEIGHTED REGRESSION

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文件名称：NONLINEAR IMAGE PROCESSING AND FILTERING A UNIFIED APPROACH BASED ON VERTICALLYWEIGHTED REGRESSION
文件大小：851KB
文件格式：PDF
更新时间：2013-02-13 11:47:14
Image filtering, vertically weighted regression, A class of nonparametric smoothing kernel methods for image processing and filtering that possess edge-preserving pro- perties 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.