Supervised image classification of multi-spectral images based on statistical machine learning

Image classification for geostatistical data is one of the most important issues in the remote-sensing community. Statistical approaches have been discussed extensively in the literature. In particular, Markov random fields (MRFs) are used for modeling distributions of land-cover classes, and contextual classifiers based on MRFs exhibit efficient performances. In addition, various classification methods were proposed. See Ref. [3] for an excellent review paper on classification. See also Refs. [1,4-7] for a general discussion on classification methods, and Refs. [8,9] for backgrounds on spatial statistics.