Contextual classification in image analysis: an assessment of accuracy of ICM

Abstract

This paper considers the performances of the ICM image classification technique contrasted with the maximum likelihood ordinary discriminant analysis (ML). The latter technique is the most widely used in an applied context by space agencies and remote sensing units. The two methods are compared in terms of the global accuracy produced and in terms of the spatial continuity properties of classification errors. ICM outperforms ML in most experimental cases in terms of the global accuracy produced. However, in some instances, it has a more marked tendency to produce classification errors that are short-distance correlated.