Nonlinear filtering of multivariate images under robust error criterion.
A class of nonlinear filters for multivariate data is introduced. A robust error criterion is minimized. Approximate algorithms for computing the filter output are developed. A polynomial signal model is used in applications where the signal amplitude has to be retained with high fidelity. Simulated data and RGB color image data are used in experiments.
Koivunen
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Dept. of Electr. Eng., Oulu Univ.