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13 March 2003 Fuzzy information fusion for the extraction of urban features based on HRSC data
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Abstract
In this paper, a technique for the automatic extraction of houses based on data from the airborne sensor HRSC-A is presented. Due to uncertainties within the given data sources (multispectral, 3D, and panchromatic information), a fuzzy approach is applied that is divided into two main processing parts and a third post-processing part. Within the first part, each information source is processed separately to achieve higher level information products for the following fusion process. A multispectral classification with a fuzzy measure extracts the posibility of each pixel to belong to an urban class. Since the necessary type of 3D information is the actual height of objects above the ground level, this information including the possibilities for different height levels are computed from the digital surface model. A watershed segmentation is used to identify homogeneous regions within the panchromatic band. The resulting segments represent the basic units for further analysis steps. Within the second part, height and spectral information of each segment are combined and improved by fuzzy rules. Uncertainties within the height information are reduced by spectral context knowledge while many spectral ambiguities are solved using reliable height information. Finally, possible house segments are extracted based upon the improved class possibilities.
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Marina Mueller and Karl Segl "Fuzzy information fusion for the extraction of urban features based on HRSC data", Proc. SPIE 4885, Image and Signal Processing for Remote Sensing VIII, (13 March 2003); https://doi.org/10.1117/12.463158
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