Log-Euclidean Kernel-Based Joint Sparse Representation for Hyperspectral Image Classification

Weidong Yang
Weidong Yang

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, pp. 5023-5034, 2019.

Cited by: 0|Bibtex|Views7|DOI:https://doi.org/10.1109/JSTARS.2019.2952408
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Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

Motivated by the superior performance of region covariance descriptor, we use covariance matrices as new features to replace the original spectral pixel features, and employ a Log-Euclidean metric to characterize the geodesic distance between symmetric positive definite (SPD) covariance matrices. Based on the covariance features and Log-E...More

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