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Title |
Support Vector Machine Training of HMT Models for Multispectral Image Classification |
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Author |
Reda A. El-Khoribi |
| Citation |
Vol. 8 No. 9 pp. 224-228 |
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Abstract |
This paper introduces a novel approach to supervised classification of multispectral images. The approach uses a new discriminative training algorithm for discrete hidden Markov tree (HMT) generative models applied to the multi-resolution ranklet transforms. System is implemented and tested on a set of Landsat 7-band images containing eight different land cover classes. Experimental results of the system show significant improvement over the baseline HMT system and give a superior performance in land cover classification. |
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Keywords |
HMT, SVM, land cover classification, discriminative training. |
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