2013 International Conference on Signal-Image Technology & Internet-Based Systems (2011)
Nov. 28, 2011 to Dec. 1, 2011
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SITIS.2011.27
This paper presents a supervised classification method applied to building change detection in VHR aerial images. Multi-spectral stereo pairs of 0.3m resolution have been processed to derive elevation, vegetation index and colour features. These features help filling a 5-dimensional histogram whose bins finally hold the ratio of built-up and non built-up pixels, according to the vector database to be updated. This ratio is used as building confidence at each pixel to issue a building confidence map from which to perform building verification and detection. The implementation based on histogram is very simple to code, very fast in execution and compares in this application to a state-of-the-art supervised classifier. It has been tested for the Belgian National Mapping Agency (IGN) to identify areas with high probability of change in building layers.
Building change detection, Digital Surface Model, multi-spectral images, histogram classification
Charles Beumier, Mahamadou Idrissa, "Building Change Detection by Histogram Classification", 2013 International Conference on Signal-Image Technology & Internet-Based Systems, vol. 00, no. , pp. 409-415, 2011, doi:10.1109/SITIS.2011.27