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Compared to conventional optical images, the classification of remote sensing SAR images represents a rather difficult task. As a rule, the various SAR imaging and product options, the high dynamic range of SAR images, and the presence of speckle noise prevent us from obtaining robust classification results. In the following, we try to circumvent these difficulties by proper pre-processing and despeckling...
Gauss-Markov random fields have been successfully used as texture models in a host of applications, ranging from synthesis, feature extraction, classification and segmentation to query by image content and information retrieval in large image databases. An issue that deserves special consideration is the selection of the neighbourhood order (model complexity), which should faithfully reflect the Markovianity...
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