Histogram-Based Contextual Classification of SAR Images

We propose a spatially dependent mixture model for contextual classification of synthetic aperture radar (SAR) images. The proposed mixture model is based on the local image histograms modeled by multinomial densities. The contextual information is included into the mixture model both in the pixel and the class label domain by using local histograms and autologistic regression, respectively. Based on the classification results obtained on real TerraSAR-X images, it is shown that the proposed model is capable of more accurately classifying the pixels particularly in the heterogeneous regions, such as urban areas, compared with the conventional mixture model.