Why can LDA be performed in PCA transformed space?

摘要

PCA plus LDA is a popular framework for linear discriminant analysis (LDA) in high dimensional and singular case. In this paper, we focus on building a theoretical foundation for this framework. Moreover, we point out the weakness of the previous LDA based methods, and suggest a complete PCA plus LDA algorithm. Experimental results on ORL face image database indicate that the proposed method is more effective than the previous ones.