When dealing with SAR image classification, the class parameters may vary along the swath for several reasons. Traditional classification algorithms are then not well adapted, as they assume constant class parameters. In this paper, we propose a binary classification algorithm based on Markov Random Fields that take into account the parameters variations in the swath, and we present results obtained on airborne TropiSAR and simulated SWOT HR data.