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Improving SVM classification accuracy using a hierarchical approach for hyperspectral images

Begm Demir, Sarp Ertrk
2009 2009 16th IEEE International Conference on Image Processing (ICIP)  
For classification, multi-level two-dimensional wavelet decomposition is applied to each hyperspectral image band and low spatial frequency components of each level are used for hierarchical classification  ...  computational load of SVM classification and provides reduced SVM testing time compared to standard SVM.  ...  and same class neighborhood property.  ... 
doi:10.1109/icip.2009.5414491 dblp:conf/icip/DemirE09 fatcat:s6utakfxx5d2zf3zktnfqewkma

Assessment of Performance Improvement in Hyperspectral Image Classification Based on Adaptive Expansion of Training Samples

Maryam Imani, Hasan Ghasemian
unpublished
The results of experiments show that proposed method can solve the limitation of training samples in hyperspectral images and improve the classification performance.  ...  A relevant problem for supervised classification of hyperspectral image is the limited availability of labeled training samples, since their collection is generally expensive, difficult and time consuming  ...  Acknowledgment This work is supported by Iranian Telecommunication Research Center (ITRC).  ... 
fatcat:ly3p3bp22jc5hiqortpngyvaue