two different methods of bayesian segmentation algorithm were used with different band combinations. sequential maximum a posteriori (smap) is a bayesian image segmentation algorithm which unlike the traditional maximum likelihood (ml) classification attempts to improve accuracy by taking contextual information into account, rather than classifying pixels separately. landsat 7 etm+ data with pa...

classifying remote sensing imageries to obtain reliable and accurate landuse/cover (luc) information still remains a challenge that depends on many factors suchas complexity of landscape especially in arid region. the aim of this paper is to extractreliable luc information from land sat imageries of the pishkouh watershed of centralarid region, iran. the classical maximum likelihood classifier ...

A spectral classification comparison was performed using four different classifiers; the parametric maximum likelihood classifier and three non-parametric classifiers; neural networks, fuzzy rules, and fuzzy neural networks. The input image data is a SPOT satellite image of the Otago Harbour near Dunedin, New Zealand. The SPOT image data contains three spectral bands in the green, red and visib...