Filament Preserving Segmentation for SAR Sea Ice Imagery Using a New Statistical Model

Modelling spatial context constraints using Markov random field (MRF) has been widely used in the segmentation of noisy images [7][10][17]. Its applicability to SAR sea ice segmentation has also been demonstrated recently [6]. However, most existing MRF models are not capable of preserving filaments, specifically leads and ridges for SAR sea ice, which are valuable for ship navigation applications and helpful for identifying certain ice types. A new statistical context model is proposed that can preserve such narrow elongated features while producing similar smooth segmentation results as those of existing MRF based approaches.