The automatic extraction of building footprints from remotely sensed images has been used for updating geospatial databases in urban areas [1]. The launch of High Resolution Spaceborne Stereo (HRSS) sensors (e.g. GeoEye, WorldView, QuickBird) started a new era by providing the possibility to obtain stereo images and 3D maps from space [2]. Indeed, building identification, reconstruction, and change detection have been carried out using stereo image matching, as well as 3D edge matching techniques [3,5-6]. As stated in [3], 3D edge matching based on stereo images delivers promising results, but only if the buildings are large enough with respect to the spatial resolution of the data, have a simple rectangular shape, and a good radiometric contrast compared to surrounding objects. As a matter of fact, although 3D edge matching using very high resolution aerial images can reconstruct building footprints in detail [7], using space-borne images the same approach may encounter issues, particularly where building outlines are not clearly detected in both epipolar images. Additionally, although image matching delivers a DSM representing buildings heights, building size and shapes extracted from this DSM are usually overestimated, so that auxiliary information is required.
A hybrid approach for delineation of building footprints from space-borne stereo images
Gamba P.;
2018-01-01
Abstract
The automatic extraction of building footprints from remotely sensed images has been used for updating geospatial databases in urban areas [1]. The launch of High Resolution Spaceborne Stereo (HRSS) sensors (e.g. GeoEye, WorldView, QuickBird) started a new era by providing the possibility to obtain stereo images and 3D maps from space [2]. Indeed, building identification, reconstruction, and change detection have been carried out using stereo image matching, as well as 3D edge matching techniques [3,5-6]. As stated in [3], 3D edge matching based on stereo images delivers promising results, but only if the buildings are large enough with respect to the spatial resolution of the data, have a simple rectangular shape, and a good radiometric contrast compared to surrounding objects. As a matter of fact, although 3D edge matching using very high resolution aerial images can reconstruct building footprints in detail [7], using space-borne images the same approach may encounter issues, particularly where building outlines are not clearly detected in both epipolar images. Additionally, although image matching delivers a DSM representing buildings heights, building size and shapes extracted from this DSM are usually overestimated, so that auxiliary information is required.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
