Accurate Urban Area Detection in Remote Sensing Images

作者：Shi Hao; Chen Liang^*; Bi Fu kun; Chen He; Yu Ying

来源：IEEE Geoscience and Remote Sensing Letters, 2015, 12(9): 1948-1952.

DOI：10.1109/LGRS.2015.2439696

• Feature extraction
• high-resolution remote sensing image
• homogeneous region extraction
• urban area detection
• weighted Gaussian voting matrix (WGVM)

Automatic urban area detection in remote sensing images is an important application in the field of earth observation. Most of the existing methods employ feature classifiers and thereby contain a data training process. Moreover, some methods cannot detect urban areas in complex scenes accurately. This letter proposes an automatic urban area detection method that uses multiple features that have different resolutions. First, a down-sampled low-resolution image is used to segment the candidate area. After the corner points of the urban area are extracted, a weighted Gaussian voting matrix technique is employed to integrate the corner points into the candidate area. Then, the edge features and homogeneous region are extracted by using the original high-resolution image. Using these results as the input, the processes of guided filtering and contrast enhancement can finally detect accurately the urban areas. This method combines multiple features, such as corner, edge, and regional characteristics, to detect the urban areas. The experimental results show that the proposed method has better detection accuracy for urban areas than the existing algorithms.

• 出版日期2015-9
• 单位北方工业大学; 云南大学; 北京理工大学