This MATLAB archive contains classical and robust versions of both kernel regression and local linear regression with optimal and heuristic bandwidth selection. Robust nonparametric smoothers have been proved effective to preserve edges in image denoising. As an extension, they are capable to estimate multivariate surfaces containing discontinuities on the basis of a random spatial sampling. A crucial problem is the design of their coefficients, in particular those of the kernels which concern robustness and allow jump preserving.

Robust Kernel Smoothing of 3D Point Spatial Data

CARLO GRILLENZONI
Software
2024-01-01

Abstract

This MATLAB archive contains classical and robust versions of both kernel regression and local linear regression with optimal and heuristic bandwidth selection. Robust nonparametric smoothers have been proved effective to preserve edges in image denoising. As an extension, they are capable to estimate multivariate surfaces containing discontinuities on the basis of a random spatial sampling. A crucial problem is the design of their coefficients, in particular those of the kernels which concern robustness and allow jump preserving.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11578/354691
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