In this paper we present the capability and real-time processing features of Median M-type KNN and Wilcoxon M-type KNN filters for the removal of impulsive noise in real-time image processing applications. Extensive simulation results in known reference images have demonstrated that the proposed filter consistently could outperform other nonlinear filters by balancing the tradeoff between noise suppression and detail preservation. The criterions used to compare performance were the PSNR and MAE. The real-time implementation of image filtering was realized in the DSP TMS320C6701. The processing time of proposed filters includes the duration of data acquisition, processing and store data. We found that the values of processing time of proposed filters depend of the image to process and do not practically vary for different noise level; these values depend also of the complex calculation of influence functions and parameters of the proposed filters and the influence functions. We simulated impulsive corrupted image sequences to demonstrate that the proposed methods potentially could provide a real-time solution to quality TV/Video Transmission.
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