Dimensionality Reduction for Hyperspectral Data Based on Pairwise Constraint Discriminative Analysis and Nonnegative Sparse Divergence
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2016.2624303
Abstract: To improve the classification accuracy of unlabeled large-scale hyperspectral data, a dimensionality reduction algorithm based on pairwise constraint discriminant analysis and nonnegative sparse divergence (PCDA-NSD) is proposed by using the feature transfer learning technology. Different… read more here.
Keywords: nonnegative sparse; hyperspectral data; divergence; constraint ... See more keywords