DSP implementation of robust filters with fine detail preserving for noise suppression using RM-estimation

In this paper, we present the real time implementation of the robust RM-estimators with different influence functions such as the cut median, Hampel, Andrews sine, Tukey and Bernoulli functions. The use of these functions in the RM algorithms provides the retention of small-size details, impulsive noise removal and multiplicative noise suppression. They demonstrated better robustness in comparison with the use of the simplest cut function. The optimal values of the parameters of such filters in presence of different noise mixture are determined. The implementation by means of use of DSP TMS320C6701 has demonstrated that the values of time processing in the case of the simplest cut function is less in comparison with another influence functions, but noise suppression is better when the proposed functions were applied.