Building extraction from GF-3 images using Wishart classification assisted by extended volume scattering model

Abstract

Building extraction is considered as one of the primary applications of urban remote-sensing. To address the misclassification issue on building extraction based on Yamaguchi decomposition, an extended volume scattering model-assisted building extraction method is proposed. Here, the HV components caused by buildings whose main surface are oriented with respect to radar beam are assigned to double bounce scattering, since the extended volume scattering model is introduced. On this basis, the complex Wishart iterative classification is introduced to develop a new method of building extraction. The proposed method is employed to process C-band full-polarimetric SAR imagery obtained by GF-3. The study results verify the efficiency and accuracy of proposed method.

Keywords

• radar polarimetry
• geophysical image processing
• iterative methods
• radar imaging
• synthetic aperture radar
• image classification
• feature extraction
• c-band full-polarimetric sar imagery
• double bounce scattering
• radar beam
• hv components
• yamaguchi decomposition
• urban remote-sensing
• building extraction method
• extended volume scattering model
• complex wishart iterative classification
• gf-3 images