SAR images filtering and segmentation: a multiresolution and contextual approach

In this work we present a mixed contextual algorithm for segmenting SAR-ERS 1 images (/spl copy/ ESA). The first step was to pre-process the original SAR image by means of a polynomial transform based filter in order to decrease the effect of speckle. Segmentation stage was performed as follows: cluster centers were obtained using a non-contextual algorithm; then, based on a Bayes classifier we achieved a first segmentation step, but defining a 'reject class'; finally, rejected pixels were e-classed via a Markovian model. Results obtained show segmented images exhibiting homogeneous regions and a minimal presence of isolated pixels. As well, they evidence that combined use of polynomial transform and Markov random field theory does not introduce a noticeable degradation of edges in segmented regions.