An Index Based on Joint Density of Corners and Line Segments for Built-Up Area Detection from High Resolution Satellite Imagery

Abstract

Detection of built-up areas from Very High Spatial Resolution (VHSR) remote sensing images is a critical step in urbanization monitoring. This paper presents a method for extracting built-up areas from VHSR remote sensing imagery by using feature-level-based fusion of right angle corners, right angle sides and road marks. This method has six main steps. First, line segments are detected. Second, the Harris corner points are detected. Third, the right-angle corners and right-angle sides are determined by cross-verification of the above detected Harris corners and line segments. Fourth, the potential road marks are detected by the template matching method. Fifth, a built-up index image is constructed. Finally, the built-up areas are extracted through a binary thresholding of the above index image. Three satellite images with wide coverage are employed for evaluating the above proposed method. The experimental results suggest that the proposed method outperforms the classic PanTex method. On average, the completeness and the quality of the proposed method are respectively 17.94% and 13.33% better than those of the PanTex method, while there is no great difference between the two methods on the correctness.

Keywords

• remote sensing
• very high spatial resolution
• satellite image
• built-up area
• Harris corners
• line segment
• spatial voting