Median based feature selective filtering

The design of a linear filter is quite straight forward especially if the spectra of the required and unwanted signals are known and do not overlap with each other. Basically, a linear filter is implemented by tuning its passband to the required signal and adjusting its stopband to the unwanted signal. However, in case of two or higher dimensional image filtering, we normally only have knowledge about the shape of the unwanted feature and have little or no knowledge about its spectrum. For non-linear filters such as the 2-D standard median filters, their filtering characteristics can only be roughly controlled by the size and the shape of the filter window. The unwanted feature cannot be specified in details and hence some related but required features may also be removed. In this paper, a novel median based feature selective filtering technique is introduced. Unwanted features of any particular shape can be specified in details by a set of custom-tailored shells and all features, other than those specified features which are to be removed, can be preserved regardless of feature orientations. In particular, this technique can be used to remove very high density impulsive noise from corrupted images.