Laplacian Regularized Kernel Canonical Correlation Ensemble for Remote Sensing Image Classification

Xiao-Zhen Luo
Xiao-Zhen Luo
Timothy Apasiba Abeo
Timothy Apasiba Abeo
Yang Yang
Yang Yang

IEEE Geoscience and Remote Sensing Letters, pp. 1150-1154, 2019.

Cited by: 2|Views28
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Abstract:

Kernel canonical correlation analysis (KCCA) is an efficient dimensionality reduction tool in the application of remote sensing image classification. However, it suffers from the problem of parametric sensitivity since a single kernel is used. In this letter, a KCCA ensemble framework is put forward to improve the robustness of KCCA. Foll...More

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