Extraction of Human Settlements from High Resolution Remote Sensing Imagery by Fusing Features of Right Angle Corners and Right Angle Sides

doi:10.11947/j.AGCS.2017.20160389

Abstract

Abstract: A method for human settlements extraction from high resolution remote sensing imagery using feature-level-based fusion of right-angle-corners and right-angle-sides is proposed in this paper. First, the corners and line segments are detected, the right-angle-corners and right-angle-sides are determined by cross verification of the detected corners and line segments, and these two types of features are rasterized. Second, a human settlement index image is built based on the density and distance of the right-angle-corners and right-angle-sides in a local region. Finally, the polygons of human settlements are generated through binary thresholding of the index image, conversion from raster format to vector format, and sieving. Three images are used for testing the proposed method. The experimental results show that our proposed method has higher accuracy than the existed method. Specifically, the correctrate, completeness, and quality of our method is higher 6.76%, 10.12%, 12.14% respectively than the existed method.

Key words: high resolution remote sensing image, human settlement, Harris corners, line segment, spatial voting

CLC Number:

P237

LIN Xiangguo, NING Xiaogang. Extraction of Human Settlements from High Resolution Remote Sensing Imagery by Fusing Features of Right Angle Corners and Right Angle Sides[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(1): 83-89.

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