Two-Dimensional Quaternion PCA and Sparse PCA

IEEE Transactions on Neural Networks and Learning Systems, pp. 2028-2042, 2018.

Cited by: 12|Views8


Benefited from quaternion representation that is able to encode the cross-channel correlation of color images, quaternion principle component analysis (QPCA) was proposed to extract features from color images while reducing the feature dimension. A quaternion covariance matrix (QCM) of input samples was constructed, and its eigenvectors w...More



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