SAR images are perfectly suited for change detection, given that they are not
affected by different sun illumination conditions and/or clouds. There is potential to improve
the SAR change detection results by taking into account prior knowledge of the scene, which
can be obtained from other sources of information such as high resolution optical images
and data from Geographic Information Systems (GIS). In this paper we will describe how
information about the scene geometry and a classification of the scene into different
semantic classes can be obtained from the optical and GIS data, and how this information
can be transformed to the slant-range coordinate system of SAR images so that it can be
easily used in the change detection process. Finally, we will show some initial results that
illustrate the benefits of using this information about the scene during the change detection.
«
SAR images are perfectly suited for change detection, given that they are not
affected by different sun illumination conditions and/or clouds. There is potential to improve
the SAR change detection results by taking into account prior knowledge of the scene, which
can be obtained from other sources of information such as high resolution optical images
and data from Geographic Information Systems (GIS). In this paper we will describe how
informat...
»