Multiple data-dependent kernel for classification of hyperspectral images
Propose a MDK for classification of hyperspectral image. Adopt centered kernel alignment (CKA) to optimize the weights of multiple basic kernels. Transform the CKA problem into quadratic programming (QP) problem. Utilize Fishers discriminant analysis (FDA) to optimize the coefficients of data dependent kernel. Transform the Fisher scalar maximization problem into generalized eigen-decomposition problem.
classification hyperspectral image (hsi) data-dependent kernel (dk) support vector machine (svm) sparse representation classifier (src)