Building detection in intricate environment based on interference suppression with digital surface model and optical image

In this paper, a remote sensing building detection method is proposed, based on knowledge of environment. Digital surface model (DSM) and optical image are utilized for analyzing intricate environment of urban area. Partitioned terrain adjustment (PTA) method is proposed for alleviating terrain interference. Furthermore, vegetation interference is suppressed by optical image based reconfirming. Experiments results indicate that high accuracy detection could be obtained by our method.

[1]  Mojca Kosmatin Fras,et al.  Classification based building detection from GeoEye-1 images , 2011, 2011 Joint Urban Remote Sensing Event.

[2]  Huseyin Gokhan Akcay,et al.  Automatic Detection of Geospatial Objects Using Multiple Hierarchical Segmentations , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Uwe Soergel,et al.  Building Detection From One Orthophoto and High-Resolution InSAR Data Using Conditional Random Fields , 2011, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[4]  Cem Ünsalan,et al.  A Probabilistic Framework to Detect Buildings in Aerial and Satellite Images , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[5]  James J. Little,et al.  A Hybrid Conditional Random Field for Estimating the Underlying Ground Surface From Airborne LiDAR Data , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[6]  Michael Cramer,et al.  The DGPF-Test on Digital Airborne Camera Evaluation - Over- view and Test Design , 2010 .