Visualization and unsupervised classification of changes in multispectral satellite imagery |
Morton J. Canty, Allan A. Nielsen
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| Abstract | The statistical techniques of multivariate alteration detection, minimum/maximum autocorrelation factors transformation, expectation maximization and probabilistic label relaxation are combined in a unified scheme to visualize and to classify changes in multispectral satellite data. The methods are demonstrated with an example involving bitemporal LANDSAT TM imagery. |
| Type | Journal paper [With referee] |
| Journal | International Journal of Remote Sensing |
| Year | 2006 Vol. 27 No. 18 pp. 3961-3975 |
| Address | Richard Petersens Plads, Building 321 |
| Series | Technical University of Denmark |
| ISBN / ISSN | DOI:10.1080/01431160500222608 |
| Electronic version(s) | [pdf] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Image Analysis & Computer Graphics, Geoinformatics |