Two-stage robust rank filter with fine detail preserving for the image processing

In this paper, we present implementation of the robust RM-estimators with different influence functions such as the cut median (skipped median) function and Hampel function. We obtained that use of these functions in the RM algorithms demonstrated better robustness in comparison with the simplest cut median function. Applications of these functions in filtering procedures provide the preservation of fine details, impulsive noise removal and suppression of the multiplicative noise. The implementation of the cut median and Hampel functions in the RM-KNN filter has shown that its use is a good tool for preservation of fine details and suppression of noise by means of use DSP TMS320C6701. The deterministic and statistical properties of the designed filters have been investigated and shown their effectiveness. The optimal values for parameters of these filters for different noise mixture are presented in this paper. Finally, DSP implementation has demonstrated that in the case of use the simplest cut median the time of processing is less than in the case of applications the cut median and Hampel functions, but noise suppression is better when cut median or Hampel functions were applied.