You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
1 April 1999Adaptive multichannel marginal L-filters
Three adaptive multichannel L-filters based on marginal data ordering are proposed. They rely on well-known algorithms for the iterative minimization of the mean square error (MSE), namely, the least mean squares (LMS), the normalized LMS (NlMs), and the LMS- Newton (LMSN) algorithms. We treat both the unconstrained minimization of the MSE and the minimization of the MSE when structural constraints are imposed on the filter coefficients. The performance 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 considered as well. Performance comparisons are made in both RGB and U*V*W* color spaces. The proposed adaptive multichannel L-filters outperform the other candidates in noise suppression for color images corrupted by mixed impulsive and additive white contaminated Gaussian noise.