Title :
Building Footprints Extraction from PolSAR Image Using Multi-Features and Edge Information
Author :
Lili Yan ; Jixian Zhang ; Guoman Huang ; Zheng Zhao
Author_Institution :
Key Lab. for Land Environ. & Disaster Monitoring of State Bur. of Surveying & Mapping, China Univ. of Min. & Technol., Xuzhou, China
Abstract :
Due to the urgent requirement on SAR image interpretation, a method to extract building footprints from PolSAR image based on polarimetric scattering features and texture features was proposed. Firstly, polarimetric scattering features are extracted by Freeman decomposition and H/A/α decomposition method. Texture features are extracted based on gray level co-occurrence matrix (GLCM). Then, support vector machine (SVM) with Gaussian kernel function is trained to detect building regions by different features sets selected. At last, building polygons extraction is implemented: Line segments are extracted from obtained building regions by radon transform; cycles corresponding to the profiles of buildings in the graph are searched after determining line segment endpoints graph; building footprints are created by eliminating false cycles and connecting component cycles. The approach was demonstrated using airborne PolSAR image. Different features sets selected from experiment data were used to extract building footprints. Comparing the extraction results, the optimum features sets fitting for building footprints were extracted. Results show that the method provides a reliable way to extract building footprints comprehensively using multi-features and edge information.
Keywords :
Gaussian processes; Radon transforms; airborne radar; feature extraction; geophysical image processing; image texture; matrix algebra; object detection; radar imaging; radar polarimetry; support vector machines; synthetic aperture radar; Freeman decomposition; GLCM; Gaussian kernel function; H-A-α decomposition method; PolSAR image interpretation; Radon transform; SVM; airborne PolSAR image; building footprint extraction; building polygon extraction; building region detection; edge information; false cycle elimination; feature extraction; gray level cooccurrence matrix; line segment endpoint graph; multifeature information; polarimetric scattering; support vector machine; Accuracy; Buildings; Data mining; Equations; Feature extraction; Scattering; Support vector machines;
Conference_Titel :
Image and Data Fusion (ISIDF), 2011 International Symposium on
Conference_Location :
Tengchong, Yunnan
Print_ISBN :
978-1-4577-0967-8
DOI :
10.1109/ISIDF.2011.6024275