
handle: 10419/61250
The paper is concerned with the problem of image denoising. We consider the case of black-white type images consisting of a finite number of regions with smooth boundaries and the image value is assumed to be piecewise constant within each region. New method of image denoising is proposed which is adaptive (assumption free) to the number of regions and smoothness properties of edges. The method is based on a pointwise image recovering and it relies on an adaptive choice of a smoothing window. It is shown that the attainable quality of estimation depends on the distance from the point of estimation to the closest boundary and on the smoothness properties of this boundary. As a consequence, it turns out that the proposed method provides the optimal rate of the edge estimation.
data-driven window, design, pointwise adaptation, edge, rate of image and edge estimation, grid, 510, averaging window -- Image and edge estimation -- pointwise adaptation, edge -- design -- grid -- image -- pointwise estimation -- rate of image and edge estimation -- data-driven window, Image analysis in multivariate analysis, 62G07, Nonparametric regression and quantile regression, image, 62G20, ddc:510, averaging window, ddc:330, edge estimation, article, Computational problems in statistics, pointwise estimation, Image and edge estimation, Density estimation, 62H35
data-driven window, design, pointwise adaptation, edge, rate of image and edge estimation, grid, 510, averaging window -- Image and edge estimation -- pointwise adaptation, edge -- design -- grid -- image -- pointwise estimation -- rate of image and edge estimation -- data-driven window, Image analysis in multivariate analysis, 62G07, Nonparametric regression and quantile regression, image, 62G20, ddc:510, averaging window, ddc:330, edge estimation, article, Computational problems in statistics, pointwise estimation, Image and edge estimation, Density estimation, 62H35
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