Fusion of polarimetric and texture information for urban building extraction from fully polarimetric SAR imagery
Building extraction from remote sensing images is very important in many fields, such as urban planning, land use investigation, damage assessment, and so on. In polarimetric synthetic aperture radar (PolSAR) imagery, the buildings not only have typical polarimetric features but also have rich texture features. In this paper, the texture information is introduced to improve the accuracy of urban building extraction from PolSAR imagery by a new method called cross reclassification .