Automated techniques for change detection using combined edge segment texture analysis, GIS, and 3D information
Autor(en): | Ehlers, M. Sofina, N. Filippovska, Y. Kada, M. |
Stichwörter: | Geographic information systems; Image analysis; Principal component analysis; Regression analysis, Automated techniques; Change detection; Multi-temporal analysis; Novel methodology; Post-classification comparisons; Principal Components; Remotely sensed images; Three categories, Image enhancement | Erscheinungsdatum: | 2014 | Herausgeber: | CRC Press | Journal: | Global Urban Monitoring and Assessment: Through Earth Observation | Startseite: | 325 | Seitenende: | 352 | Zusammenfassung: | A large number of algorithms for change detection from multitemporal remotely sensed images have been developed and applied. An overview and comparison of different methods can be found, for example, in Coppin et al. (2004), Lu et al. (2003), Mas (1999), Macleod and Congalton (1998), and Singh (1989). In general, change detection methods can be divided into three categories (Mas, 1999): (1) image enhancement methods, (2) multitemporal analysis, and (3) postclassification comparison. Other approaches combine several methods or consist of novel methodologies (an overview can be found in Lu et al., 2003). Image enhancement methods combine data mathematically to enhance image quality (Im et al., 2008). Examples include standards methods such as image difference, image ratio, and principal component and regression analysis. © 2014 by Taylor & Francis Group, LLC. |
ISBN: | 9781466564503 9781466564497 |
Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84923293716&partnerID=40&md5=037e826d744a67ae8fca83c854466cff |
Zur Langanzeige
Seitenaufrufe
15
Letzte Woche
0
0
Letzter Monat
0
0
geprüft am 17.05.2024