Name
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1080/10095020.2015.1127628 | GEO-SPATIAL INFORMATION SCIENCE |
Keywords | Field | DocType |
aerial images,water,specular reflection,hot spots,radiometric normalization | Computer vision,Normalization (statistics),Remote sensing,Specular reflection,Artificial intelligence,Region growing,Water body,Seeding,Brightness,Mathematics,Relative standard deviation | Journal |
Volume | Issue | ISSN |
19.0 | 1 | 1009-5020 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
2 | ||