Bruzzone, Lorenzo and Fernandez Prieto, Diego (2002) A partially unsupervised cascade classifier for the analysis of multitemporal remote-sensing images. UNSPECIFIED. (Unpublished)
Abstract
A partially unsupervised approach to the classification of multitemporal remote-sensing images is presented. Such an approach allows the automatic classification of a remote-sensing image for which training data are not available, drawing on the information derived from an image acquired in the same area at a previous time. In particular, the proposed technique is based on a cascade classifier approach and on a specific formulation of the expectation-maximization (EM) algorithm used for the unsupervised estimation of the statistical parameters of the image to be classified. The results of experiments carried out on a multitemporal data set confirm the validity of the proposed approach.
| Item Type: | Departmental Technical Report |
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| Department or Research center: | Information Engineering and Computer Science |
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| Subjects: | T Technology > T Technology (General) |
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| Uncontrolled Keywords: | Multitemporal classification, cascade classifier, unsupervised parameter estimation, remote sensing |
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| Additional Information: | Submitted to Pattern Recognition Letters |
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| Report Number: | DIT-02-029 |
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| Repository staff approval on: | 21 Jan 2003 |
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