Name
Abstract | ||
|---|---|---|
Automatic building extraction is an important field of research in remote sensing. This letter introduces a new object-based building extraction approach. So far, many object-based algorithms for building extraction have been proposed. However, these algorithms mainly operate in two phases: object construction and building extraction. The majority of these algorithms heavily relies on the object construction process, mainly due to the lack of interaction between the two steps. To overcome these drawbacks, we introduce a new hierarchical approach based on building templates. Carried out experiments on data sets of images from the urban area of Strasbourg show the benefits of our approach. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/LGRS.2013.2276936 | Geoscience and Remote Sensing Letters, IEEE |
Keywords | Field | DocType |
buildings (structures),feature extraction,geophysical image processing,object recognition,remote sensing,automatic building extraction,building template,hierarchical approach,object construction,remote sensing,template based hierarchical building extraction,Building,cooperation,dynamic template,object-based | Computer vision,Data mining,Data set,Remote sensing,Feature extraction,Artificial intelligence,Template,Mathematics,Cognitive neuroscience of visual object recognition | Journal |
Volume | Issue | ISSN |
11 | 3 | 1545-598X |
Citations | PageRank | References |
1 | 0.40 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aymen Sellaouti | 1 | 6 | 1.72 |
| Atef Hamouda | 2 | 40 | 12.57 |
| Aline Deruyver | 3 | 77 | 11.56 |
| Cédric Wemmert | 4 | 96 | 15.05 |