Image enhancement using the median and the interquartile distance

Enhancement and noise cleaning algorithms based on local medians and interquartile distances are more effective than those using local means and standard deviations for the removal of spikelike noise, preserve edge sharpness better, and introduce fewer artifacts around high contrast edges present in the original data. They are usually not as fast as the mean-standard deviation equivalents, but all are suitable for large data sets to be treated in small machines in production quantities.