Impulsive noise suppression and analysis in color imaging

We present the analysis and simulation results for some modifications of the vectorial color imaging procedures those use at the second stage of magnitude processing the different order statistics filters. The technique of non-parametric filtering is presented and investigated in this paper too. For unknown functional form of noise density estimated from the observations we use the gray scalar filters to provide the reference vectors needed to realize the calculations. The performances of the traditional order statistics algorithms such as, median, Vector Median, alfa-trimmed mean, Wilcoxon, other order statistics M KNN are analyzed in the paper. For comparison analysis of the color imaging we use the following enterions: MAE; PSNR; MCRE; NCD Numerous simulation results which characterize the impulsive noise suppression and fine detail preservation are presented in the paper using different test images) such as: Lena, Mandrill, Peppers, etc. (256×256, 24 bits, RGB space). The algorithms those demonstrated good performance results have been applied to process the video sequences: "Miss America", "Flowers" and Foreman corrupted by impulsive noise. The results of the simulations presented in the paper show differences in color imaging by mentioned filtering technique and help to choose the filter that can satisfy to several criterion at dependence on noise level value.