Fuzzy Super Resolution Mapping Based on Markov Random Fields

Recent research has used Markov Random Fields (MRF) as a method for super-resolution mapping (SRM). This paper investigated the per-pixel uncertainty associated with MRF based SRM. This provided insight into the spatial distribution of uncertainty associated with SRM. Furthermore, the map of per-pixel uncertainty clearly shows the boundary between land-cover classes and this may provide an input for image segmentation. The insight provided by the per-pixel uncertainty together with the class boundaries will be valuable for development of the MRF approach to super-resolution mapping.