Object-based Morphological Building Index for Building Extraction from High Resolution Remote Sensing Imagery

doi:10.11947/j.AGCS.2017.20170068

Abstract

Abstract: Building extraction from high resolution remote sensing images is a hot research topic in the field of photogrammetry and remote sensing. In this article, an object-based morphological building index (OBMBI) is constructed based on both image segmentation and graph-based top-hat reconstruction, and OBMBI is used for building extraction from high resolution remote sensing images. First, bidirectional mapping relationship between pixels, objects and graph-nodes are constructed. Second, the OBMBI image is built based on both graph-based top-hat reconstruction and the above mapping relationship. Third, a binary thresholding is performed on the OBMBI image, and the binary image is converted into vector format to derive the building polygons. Finally, the post-processing is made to optimize the extracted building polygons. Two images, including an aerial image and a panchromatic satellite image, are used to test both the proposed method and classic PanTex method. The experimental results suggest that our proposed method has a higher accuracy in building extraction than the classic PanTex method. On average, the correctness, the completeness and the quality of our method are respectively 9.49%, 11.26% and 14.11% better than those of the PanTex.

Key words: high resolution remote sensing image, building extraction, region adjacency graph, mathematical morphology, object-based image analysis

CLC Number:

P237

LIN Xiangguo, ZHANG Jixian. Object-based Morphological Building Index for Building Extraction from High Resolution Remote Sensing Imagery[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(6): 724-733.

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