New partition-based filters for suppressing mixed high probability impulse and Gaussian noises in images

In this paper, we propose a new partition-based filter for removing mixed high probability impulse and Gaussian noises by extraction of the signals. The proposed filter sorts the elements of the sample vector and extracts the signals around the median from the sorted signals. The extraction vector is classified into one of M partitions, and a particular filtering operation is then activated. The output of the filter is estimated by the current pixel and the extraction vector. Carrying out the simulation, we illustrate the peak signal to noise ratio of the proposed filter, and show that it is effective in removing mixed high probability impulse and Gaussian noises.