Curvelet based feature extraction of dynamic ice from SAR imagery

Abstract

Synthetic Aperture Radar (SAR) images of sea ice have proven to be very useful toward classification of ice cover into ice types. However, using SAR images to separate the marginal ice zone (MIZ) from consolidated ice and open water has not been explicitly considered before. One typical feature of MIZ is that it is more dynamic than consolidated ice, and includes floes, fast and thin ice or ice eddies. The current paper utilizes the dynamic feature of MIZ to investigate a curvelet-based feature extraction method in order to classify a SAR image into open water, dynamic ice and consolidated ice, as a first step toward using SAR imagery to identify the MIZ. An experiment of 10-fold cross validation is conducted to demonstrate that the proposed feature extraction method is effective. Finally, an SVM classifier is used on a SAR image to test the performance of the curvelet-based feature. The result shows that curvelet-based feature can classify the dynamic ice accurately.