Title :
Nonlinear filtering of multivariate images under robust error criterion
Author_Institution :
Dept. of Electr. Eng., Oulu Univ., Finland
fDate :
6/1/1996 12:00:00 AM
Abstract :
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
Keywords :
error analysis; image processing; nonlinear filters; polynomials; RGB color image data; approximate algorithms; filter output; high fidelity; image processing; multivariate images; nonlinear filtering; polynomial signal model; robust error criterion; signal amplitude; simulated data; Additive noise; Color; Colored noise; Computational modeling; Filtering; Image processing; Nonlinear filters; Polynomials; Robustness; Statistics;
Journal_Title :
Image Processing, IEEE Transactions on
