Liu H, Yang M, Chen J, et al. Line-constrained shape feature for building change detection in VHR remote sensing imagery[J]. ISPRS International Journal of Geo-Information, 2018, 7(10): 410.[DOI：10.3390/ijgi7100410]
发布时间：2021-06-18
点击次数：
摘要：Buildings represent the most relevant features of human activity in urban regions, but their change detection using very-high-resolution (VHR) remote sensing imagery is still a major challenge. Effective representation of the building is the key point in building change detection. The linear feature can indirectly represent the structure and distribution of man-made objects. Thus, this study proposes a shape feature-based building change detection method. Specifically, a line-constrained shape (LCS) feature is developed to capture the shape characteristics of buildings. This feature improves the discriminability between buildings and other ground objects by integrating the pixel shape feature and line segments. The building candidate area (BCA) is created in accordance with the distribution of the line segments in two-phase images. The problem space is constrained in a high-likelihood region of buildings because of the BCA. Comparative experimental results demonstrate that the combination of the spectral feature and the developed LCS feature achieves the best performance in object-based building change detection in VHR imagery.
论文类型：期刊论文
是否译文：否
收录刊物：SCI
发布期刊链接：https://www.mdpi.com/2220-9964/7/10/410
上一条： Chen J, Han Y, Wan L, et al. Geospatial relation captioning for high-spatial-resolution images by using an attention-based neural network[J]. International Journal of Remote Sensing, 2019, 40(16): 6482-6498.[DOI:10.1080/01431161.2019.1594439]
下一条： Chen J, Liu H, Hou J, et al. Improving Building Change Detection in VHR Remote Sensing Imagery by Combining Coarse Location and Co-Segmentation[J]. ISPRS International Journal of Geo-Information, 2018, 7(6): 213.[DOI：10.3390/ijgi7060213]