Bayesian Classification of Surface-Based Ice-Radar Images

This paper deals with the application of the Bayes classification procedure to discriminate types of sea ice based on images obtained from surface-based marine radars. The data sets were digitized images obtained from a dual-polarized Ku-band radar (16 GHz) and a likepolarized S-band radar (3 GHz) at a site located on the northern tip of Baffin Island, Canada. The images were first range-compensated, and statistical properties of different ice types were then determined. The observed histograms for different ice types were approximated by continuous density functions. The images were classified by maximizing the a posteriori probabilities obtained from Bayes's rule. The results reported herein suggest that there is sufficient information in the reflectivity to classify the different forms of ice using decision theoretic pattern recognition techniques. Copyright © 1987 by The Institute of Electrical and Electronics Engineers, Inc.