Adaptive majority filtering for contextual classification of remote sensing data

This Letter presents an adapiive contexiual filler, developed by Ihe addition of a heterogeneity rule and a confidence rule to The conventional majority filter. Experiments have been carried out using a Landsat Thematic Mapper (TM) image. Results show that the adaptive majority filter has a capability of reducing the classification errors due to spectrally mixed pixels and preserves The connection of thin features. The proposed filler needs only a moderate increase in processing time compared with the conventional majority filter.