Unsupervised classification of changes in multispectral satellite imagery |
Morton J. Canty, Allan A. Nielsen
|
| Abstract | The statistical techniques of multivariate alteration detection, maximum autocorrelation factor transformation, expectation maximization, fuzzy maximum likelihood estimation and probabilistic label relaxation are combined in a unified scheme to classify changes in multispectral satellite data. An example involving bitemporal LANDSAT TM imagery is given. |
| Keywords | change detection; clustering |
| Type | Conference paper [With referee] |
| Conference | Proceedings of SPIE, Image and Signal Processing for Remote Sensing X |
| Editors | Lorenzo Bruzzone |
| Year | 2004 Month September Vol. 5573 pp. 356-363 |
| Address | Maspalomas, Gran Canaria, Spain |
| Series | Technical University of Denmark |
| Electronic version(s) | [pdf] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Image Analysis & Computer Graphics, Geoinformatics |