Individual Building Rooftop Segmentation from High-resolution Urban Single Multispectral Image Using Superpixels

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This paper proposes an algorithm to segment individual building rooftops from optical photographs based on superpixels. A novel method based on image complexity is proposed to calculate the number of superpixels and refine their boundaries. In order to differentiate buildings from ground and roads, the salient feature vectors are built by using features extracted from refined superpixels. In particular, those feature vectors are used to classify refined superpixels as object or non-object. Our segmentation algorithm is compared with two other state-of-the-art segmentation algorithms in terms of the recall and precision. Experiments show that the proposed method can segment building rooftops appropriately, yielding higher precision and better recall rates.