Markov Random Fields for SAR Remote Sensing Applications
This article aims at illustrating the powerfulness of Bayesian and
specially Markovian frameworks for different remote sensing applications and in particular
for SAR (Synthetic Aperture Radar) image processing. Indeed, the Markovian model
is a very convenient way to introduce prior knowledge on the problem to solve. It
will first be evoked with examples on the pixel level like filtering, segmentation
and classification. Then higher level applications, like object recognition, and
global image interpretation will be developed.