A novel algorithm based on the sigma filter for processing multicomponent images is proposed. The noise suppression ability ofthe proposed vector filtering algorithm is better than, e.g., that of the standard sigma filter. Moreover, the added mothfications make the filter able to remove impulsive noise. The proposed vector filter takes into account the mutual correlation between image components and preserves object edges and fine details even when the contrasts of the component images of multichaimel data are low. The comparative analysis of filter performance is done both visualiy and using several quantitative criteria. Both simulated and real color and multichaimel radar images are studied. It is shown that the modified vector sigma filter outperforms many component and vector filters. Two modifications are considered -for cases of additive and multiplicative noise. Examples of the filter performance for processing real images formed by multipolarization/multifrequency side-look aperture radars are presented.
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