Baatz, M. and Schape, A. (2000) Multiresolution Segmentation: An Optimization Approach for High Quality Multi-Scale Image Segmentation. In: Strobl, J., Blaschke, T. and Griesbner, G., Eds., Angewandte Geographische Informations-Verarbeitung, XII, Wichmann Verlag, Karlsruhe, Germany, 12-23.

has been cited by the following article:

• TITLE: Segment-Based Terrain Filtering Technique for Elevation-Based Building Detection in VHR Remote Sensing Images

  AUTHORS: Alaeldin Suliman, Yun Zhang

  KEYWORDS: Building Detection, Terrain Filtering, Elevation Normalization, VHR Imagery

  JOURNAL NAME: Advances in Remote Sensing, Vol.5 No.3, September 26, 2016

  ABSTRACT: Building detection in very high resolution (VHR) remote sensing images is crucial for many urban planning and management applications. Since buildings are elevated objects, the incorporation of elevation data provides a mean to reliable detection. However, almost all existing methods of elevation-based building detection must first generate a normalized Digital Surface Model (nDSM). This model is generated by processes of extracting and subtracting terrain elevations from the DSM data. The generation of accurate nDSM is still a challenging task to some extent. This paper introduces a segment-based terrain filtering (SegTF) technique to filter out the terrain elevations directly using DSM elevations. This technique has four steps: elevation co-registration, image segmentation, slope calculation, and building detection. These steps of the developed technique were applied to a dataset that consisted of a VHR image and a corresponding DSM for detecting buildings. The result of the building detection was evaluated and found to be 100% correct with an overall detection quality of 93%. These values indicate a highly reliable and promising technique for mapping buildings in VHR images.