Color image and video sequence restoration and improvement are complicated due to presence of various kinds of random noise. Impulsive noise is introduced by acquisition or broadcasting errors into communication channels. Non linear filters can provide good performance in terms of the signal-to-noise ratio in different levels of corruption as soon as minimum error chromaticity and minimum perceptual error. This paper presents the capability and real-time processing features of several processing techniques such as “directional processing”, “non parametric approaches” and “order statistics” filters. Some of such the filters were: Median Filter (MF), Vector Median Filter (VMF), -Trimmed Mean Filter (ATMF), Generalized Vector Directional Filter (GVDF), Adaptive Multichannel Non Parametric Filter (AMNF), Median M-type K-Nearest Neighbour (MM-KNN) filter, Wilcoxon M-type K-Nearest Neighbour (WM-KNN) filter, Ansari-Bradley-Siegel-Tukey M-Type K-Nearest Neighbor (ABSTM-KNN) filter, etc.
Extensive simulations in reference color RGB images “Lena”, “Mandrill”, “Peppers” and QCIF format video sequences (Miss America, Flowers and Foreman) have demonstrated that the proposed filters consistently can outperform the known nonlinear filters. The used performance criteria in color imaging were the traditional ones: PSNR, MAE and other specific for color imaging, NCD and MCRE. The real-time implementation of image filtering was realized on the DSP TMS320C6701. The processing time of proposed filters includes the duration of data acquisition, processing and store data. We simulated impulse corrupted color image QCIF sequences to demonstrate that some of the proposed and analyzing filters potentially could provide on line processing to quality video transmission of the images.