Descriptor correlation analysis for remote sensing image multi-scale classification
This paper addresses the problem of remote sensing image multi-scale classification by: (i) showing that using multiple scales does improve classification results, but not all scales have the same importance; (ii) showing that image descriptors do not offer the same contribution at all scales, as co...
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| creator | dos Santos, J. A. Faria, F. A. da S Torres, R. Rocha, A. Gosselin, P-H Philipp-Foliguet, S. Falcao, A. |
| description | This paper addresses the problem of remote sensing image multi-scale classification by: (i) showing that using multiple scales does improve classification results, but not all scales have the same importance; (ii) showing that image descriptors do not offer the same contribution at all scales, as commonly thought, and some of them are very correlated; (iii) introducing a simple approach to automatically select segmentation scales, descriptors, and classifiers based on correlation and accuracy analysis. |
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| language | eng |
| recordid | cdi_ieee_primary_6460815 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Accuracy Correlation Image color analysis Image segmentation Indexes Remote sensing Training |
| title | Descriptor correlation analysis for remote sensing image multi-scale classification |
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