Object Extraction from High-Resolution Multisensor Image Data

An approach to the combined extraction of linear as well as areal objects from multisensor image data based on a featureand object-level fusion is proposed. Data sources are high-resolution panchromatic digital orthoimages, multispectral image data, and interferometric SAR data. Rural test areas consisting of a road network, agricultural fields, and small villages were investigated. Road networks are extracted from the panchromatic orthoimage and from selected multispectral bands. Based on the knowledge that roads compose networks the extraction results are combined. Areal objects are extracted from multispectral data. The SAR data are segmented using image intensity and interferometric elevation. The classifications of the multispectral and SAR data are combined with the extracted road network using ruleand segment-based methods. In the outlook, comments are given on the trade-off between the improvement of the results using the new method and the increasing costs for data acquisition.