Cascaded RM-filter for remote sensing imaging

In this paper, we present the robust Cascaded AM-filter that be able to remove the mixture of impulsive and multiplicative noise in the remote sensing imaging. The designed filter uses combined R- and M- estimators called RM-estimators. The Cascaded RM-filter is the consequential connection of two filters. The first filter employs one of the proposed the RM-KNN (MM-KNN, WM-KNN, ABSTM-KNN or MoodM-KNN) filters to provide the impulsive noise rejection and detail preservation. The second filter uses an M-filter to realize multiplicative noise suppression. We apply the simplest cut, Hampel 's three part redescending, Andrew's sine, Tukey biweight, and Bernoulli influence functions in the designed filter. Extensive simulations have demonstrated that the Cascaded AM-filter consistently outperforms other filters by balancing the tradeoff between noise suppression and fine detail preservation. Finally, we have presented the implementation of proposed filter on the DSP TMS320C6701 demonstrating that it potentially provides a real-time solution in the processing of the SAR images.