Abstract
In the polar region, it is difficult to discriminate between clouds and ground surface from satellite visible or infrared data, because of the high albedo and low surface temperature of snow and ice cover. In this paper, a method to extract clouds from the surface is proposed. This study is based upon analysis of the NOAA/AVHRR infrared images in Antarctica. The algorithm consists of two major approaches : extraction of image features and a classification algorithm. Minimum distance classifier was applied to extract clouds from sea ice and ground using some image features. To improve the classification accuracy, threshold boundaries for minimum distance classifier were changed. In this way, misclassified areas were decreased without decreasing classified area.
