Paper
4 December 1998 Building detection from high-resolution color images
Stephane Girard, Philippe Guerin, Henri Maitre, Michel Roux
Author Affiliations +
Abstract
We describe a new method for the detection and reconstruction of building in dense urban areas using high resolution aerial images. Our approach begins with the generation of a dense digital elevation model (DEM). A sparse disparity map is densified using a region-based segmentation of the left aerial image: each detected region is tested to be planar in the disparity map. A strategy is proposed to optimize the generation of these planar surfaces taking into account the noise present in the sparse disparity map and the robustness and complexity of different algorithms for planar approximation. The second step of our approach deals with the generation of building hypotheses. Based on the DEM previously computed, geometric and colorimetric criteria are used for the fusion of parallel regions, for the detection of symmetrical regions in the 3D object space and for the reconstruction of roof buildings. Experimental results are presented on a scene in the suburb of Bruxelles with color images at the resolution of 10 cm/pixel.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephane Girard, Philippe Guerin, Henri Maitre, and Michel Roux "Building detection from high-resolution color images", Proc. SPIE 3500, Image and Signal Processing for Remote Sensing IV, (4 December 1998); https://doi.org/10.1117/12.331872
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CITATIONS
Cited by 13 scholarly publications.
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KEYWORDS
Image segmentation

Image resolution

Reconstruction algorithms

Error analysis

Image fusion

Image processing algorithms and systems

Data modeling

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