A heuristic method to use ice andwater probabilities from SAR imagery to improve ice concentration estimates

Accurate and detailed information of sea ice is crucial for navigation in ice-covered waters. Synthetic Aperture Radar (SAR) has been used as an effective tool in remote sensing to collect information for estimating the sea ice state. Image analysis experts produce manual image analysis charts based on their interpretation of the SAR imagery. Since the manual analysis is very time-consuming automatic methods can be used to discriminate ice-ocean and accelerate the task. Image texture features from Grey Level Co-occurrence Matrix (GLCM) are used as a source of information for ice-water discrimination. In this work an ice-concentration from RIPS is used as the background state which is updated using probabilities of ice and water calculated using GLCM texture features from the SAR image.