Title : 
High resolution SAR building detection with scene context priming
         
        
            Author : 
Yongfeng Cao ; Caixia Su ; Jianjuan Liang
         
        
            Author_Institution : 
Sch. of Math. & Comput. Sci., Guizhou Normal Univ., Guiyang, China
         
        
        
        
        
        
        
            Abstract : 
Building detection is the key step in urban information analysis from high resolution SAR images. Exploring context information is very helpful for object extraction. A method for detecting building units from high resolution SAR images with context information priming is proposed. It tries to use scene category information to prime building detection. Different building detection configurations are used for two different classes of regions. Final result is got by fusing the two different results. The two classes of regions are classified based on features of bright patches. Experiments on a TerraSAR-X intensity image covering part of Wuhan city of China with spatial resolution 1.25m*1.25m have shown the good performance of the method.
         
        
            Keywords : 
feature extraction; image resolution; radar imaging; synthetic aperture radar; China; TerraSAR-X intensity image; Wuhan city; bright patches; building detection; building detection configurations; context information priming; high resolution SAR building detection; high resolution SAR images; object extraction; scene context priming; spatial resolution; synthetic aperture radar; Context informatio; High resolution SAR image; building detection; object detection;
         
        
        
        
            Conference_Titel : 
Signal Processing (ICSP), 2012 IEEE 11th International Conference on
         
        
            Conference_Location : 
Beijing
         
        
        
            Print_ISBN : 
978-1-4673-2196-9
         
        
        
            DOI : 
10.1109/ICoSP.2012.6491927