Improved seeded region growing for detection of water bodies in aerial images |
| |
| Authors: | Jun Pan |
| |
| Institution: | 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China;2. Collaborative Innovation Center for Geospatial Technology, Wuhan University, 129 Luoyu Road, Wuhan 430079, China |
| |
| Abstract: | In aerial images, near-specular and specular reflection often appear in water bodies. They often lead to irregular brightness or color changes in water bodies and even produce hot spots, harmful to radiometric normalization. Therefore, water bodies must be eliminated when calculating radiometric differences during radiometric normalization of aerial images. In this paper, a simple method to detect water bodies in aerial images based on texture features is presented, an improved seeded region growing (SRG) method. A texture feature is calculated using the relative standard deviation index (RSDI) and a coarse-to-fine procedure is employed. The proposed method includes a multiple partition strategy and a refinement in gradient image that improves the reliability and accuracy of water body detection. By fusing water bodies detected in multiple images, hot spots in these water bodies are also detected. Experiments validate the feasibility and effectiveness of the proposed method. |
| |
| Keywords: | aerial images water specular reflection hot spots radiometric normalization |
|
|
