We consider the tensor-based spectral-spatial feature\ud
extraction problem for hyperspectral image classification.\ud
First, a tensor framework based on circular convolution is proposed.\ud
Based on this framework, we extend the traditional PCA to\ud
its tensorial version TPCA, which is applied to the spectral-spatial\ud
features of hyperspectral image data. The experiments show\ud
that the classification accuracy obtained using TPCA features\ud
is significantly higher than the accuracies obtained by its rivals