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[An unsupervised method of extracting constructions from color remote sensed image based on mean shift and neutrosophic set].

The diversity of spectral and textural information of constructions has become an obstacle in automatically detecting buildings. To overcome that, a method to detect constructions based on remote sensed images is proposed. It synthesizes neutrosophic set and mean shift algorithms to segment images transformed to neutrosophic set domain. After segmentation, an image is generated whose pixels mainly describe spectral categories based on main land features. Constructions can be extracted by generated spectral information. The algorithm overcomes the shortcomings of low stability, spectral discontinuity and complicated spectral information by enhancing and segmenting image in neutrosophic set domain. It avoids operations of extracting connected area before recognizing land features as well. Experiments show that the proposed algorithm can not only extract entire constructions steadily, precisely, completely and simply but also satisfies the demand of extracting constructions from high resolution remote sensing images.