Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 283-287, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-283-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 283-287, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-283-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

STUDY ON BUILDING EXTRACTION FROM HIGH-RESOLUTION IMAGES USING MBI

Z. Ding, X. Q. Wang, Y. L. Li, and S. S. Zhang Z. Ding et al.
  • Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, National Eng.Research Center of satellite spatial information technology, Fuzhou University, China

Keywords: Building Extraction, Morphological Building Index, Feature Extraction, High Resolution, Mathematical Morphology

Abstract. Building extraction from high resolution remote sensing images is a hot research topic in the field of photogrammetry and remote sensing. However, the diversity and complexity of buildings make building extraction methods still face challenges in terms of accuracy, efficiency, and so on. In this study, a new building extraction framework based on MBI and combined with image segmentation techniques, spectral constraint, shadow constraint, and shape constraint is proposed. In order to verify the proposed method, worldview-2, GF-2, GF-1 remote sensing images covered Xiamen Software Park were used for building extraction experiments. Experimental results indicate that the proposed method improve the original MBI significantly, and the correct rate is over 86 %. Furthermore, the proposed framework reduces the false alarms by 42 % on average compared to the performance of the original MBI.