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Stereo-based building detection in very high resolution satellite imagery using IHS color system
Automatic detection of buildings out of urban objects is not a straightforward task due to the existing spectral and textural similarities. The problem gets even worse in buildings with pitched roofs. Pitched roof buildings receive dissimilar amount of solar radiation on their different faces causing different brightness values for a single roof. Thus, in object based classification methods, each side will probably be assigned to different segments preventing proper building boundary detection. In this study, in order to detect the proper building boundaries through image segmentation, IHS (Intensity, Hue, and Saturation) color system is used. Then, to detect buildings out of the segmented image, elevation information extracted from stereo satellite imagery is benefited. The presented method was tested on GeoEye stereo imagery and 92% of the image buildings were detected precisely.
Stereo-based building detection in very high resolution satellite imagery using IHS color system
Automatic detection of buildings out of urban objects is not a straightforward task due to the existing spectral and textural similarities. The problem gets even worse in buildings with pitched roofs. Pitched roof buildings receive dissimilar amount of solar radiation on their different faces causing different brightness values for a single roof. Thus, in object based classification methods, each side will probably be assigned to different segments preventing proper building boundary detection. In this study, in order to detect the proper building boundaries through image segmentation, IHS (Intensity, Hue, and Saturation) color system is used. Then, to detect buildings out of the segmented image, elevation information extracted from stereo satellite imagery is benefited. The presented method was tested on GeoEye stereo imagery and 92% of the image buildings were detected precisely.
Stereo-based building detection in very high resolution satellite imagery using IHS color system
Jabari, Shabnam (Autor:in) / Zhang, Yun (Autor:in) / Suliman, Alaeldin (Autor:in)
01.07.2014
684168 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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