Adaptive multichannel marginal L-filters

Three adaptive multichannel L-filters based on marginal data ordering are p roposed. They rely on well-known algorithms for the iterative minimization of the mean square error (MSE), namely, the least mean squares (LMS), the n ormalized LMS (NLMS), and the LMS-Newton (LMSN) algorithms. We treat both t he unconstrained minimization of the MSE and the minimization of the MSE wh en structural constraints are imposed on the filter coefficients. The perfo rmance of the proposed adaptive multichannel L-filters is compared to that of other multivariate nonlinear filters in color image filtering. Adaptive multichannel linear filters and adaptive single-channel L-filters are consi dered as well. Performance comparisons are made in both RGB and U*V*W* colo r spaces. The proposed adaptive multichannel L-filters outperform the other candidates in noise suppression for color images corrupted by mixed impuls ive and additive white contaminated Gaussian noise. (C) 1999 Society of Pho to-Optical instrumentation Engineers. [S0091-3286(99)01904-2].