Abstract
An approach to building area extraction from high-resolution remote sensing imagery is proposed based on the local gradient orientation density function (LGODF) and the bimodal density function (BDF). Firstly, the LGODF is calculated by moving the window of 35 × 35 based on the gradient magnitude and the gradient direction of each pixel in the image. Then, the BDF is obtained by multiplying the movable bimodal Gaussian mixture function and LGODF in each window. Finally, peaks with difference of 90° are searched for in the BDF, and the central point of the corresponding windows are determined as building pixels. For the validity of the proposed method, seven representative sub-images from PLEIADES images covering Shenzhen China are selected. Experimental results reveal that the precision achieve 94.08% and the recall up to 96.70%.
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Acknowledgments
This work was supported by National Natural Science Foundation of China (Grant No. 41701491), Natural Science Foundation of Fujian Province, China (Grant No. 2017 J01464), Special Funds of the Central Government Guiding Local Science and Technology Development (2017 L3009) and Program for Changjiang Scholars and Innovative Research Team in University (Grant No. IRT_15R10).
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Communicated by: H. Babaie
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Shi, W., Mao, Z. & Liu, J. Building area extraction from the high spatial resolution remote sensing imagery. Earth Sci Inform 12, 19–29 (2019). https://doi.org/10.1007/s12145-018-0355-5
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DOI: https://doi.org/10.1007/s12145-018-0355-5