Periodic building change detection is important for many applications, including disaster management. Building map databases need to be updated based on detected changes so as to ensure their currency and usefulness. This paper first presents a graphical user interface (GUI) developed to support the creation of a building database from building footprints automatically extracted from LiDAR (lig...

The automated building detection in aerial images is a fundamental problem encountered in aerial and satellite images analysis. Recently, thanks to the advances in feature descriptions, Region-based CNN model (R-CNN) for object detection is receiving an increasing attention. Despite the excellent performance in object detection, it is problematic to directly leverage the features of R-CNN model...

study on polsar target detection essentially requires the cattering information and polarimetric statistical data. theoretical analysis shows that some terms of the second order scattering matrices such as coherence and covariance matrix clearly show the differences between nonsymmetrical man-made objects and natural clatters which being reflection symmetric. using the model derived from these ...

Building data are one of the important data types in a topographic database. Building change detection after a period of time is necessary for many applications, such as identification of informal settlements. Based on the detected changes, the database has to be updated to ensure its usefulness. This paper proposes an improved building detection technique, which is a prerequisite for many buil...

Textons are known to be powerful operators in capturing textural properties of image regions. This paper proposes a new method to consistently combine structural cues as well as color information in an unified framework of color textons. They are used as features to detect buildings from optical imagery. Despite the simple classification algorithm, presented results are promising and show the u...