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- aggregation classification "A1".
- aggregation creator B502851.
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2009".
- aggregation format "application/pdf".
- aggregation hasFormat 539526.bibtex.
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- aggregation isPartOf urn:issn:0099-1112.
- aggregation language "eng".
- aggregation publisher "American Society for Photogrammetry and remote sensing".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Technology and Engineering".
- aggregation title "An assessment of geometric activity features for per-pixel classification of urban man-made objects using very high resolution satellite imagery".
- aggregation abstract "In this paper, we propose the use of Geometric Activity (GA) features for detecting man-made objects in urban areas using VHR satellite imagery. These features describe the geometric context of a pixel without the necessity of segmentation and can be integrated as extra bands in a per-pixel classification. Two main types of GA features were investigated: ridge features based on the well-known facet model and morphological features obtained by applying closing transforms with structuring elements of different size and shape. Our findings show a substantial increase in classification accuracy for the man-made object classes "roads and buildings with dark roof" after inclusion of GA features. Next to GA features, the use of object-based features derived from eCognition(R), containing both geometric and textural information, was also investigated for per-pixel classification. Accuracies obtained with object-based features are comparable to the accuracies obtained with GA features. The inclusion of both GA features and object-based features further improves the overall accuracy. GA features and object-based features thus contain complementary information.".
- aggregation authorList BK843097.
- aggregation endPage "411".
- aggregation issue "4".
- aggregation startPage "397".
- aggregation volume "75".
- aggregation aggregates 604074.
- aggregation isDescribedBy 539526.
- aggregation similarTo LU-539526.