Normalization and preimage problem in gaussian kernel PCA

Kernel PCA has received a lot of attention over the past years and showed usefull for many image processing problems. In this paper we analyse the issue of normalization in Kernel PCA for the pre-image problem. We present a geometric interpretation of the normalization process for the gaussian kernel. As a consequence, we could formulate a correct normalization criterion in centered feature space. Furthermore, we show how the proposed normalization criterion improves previous pre-image methods for the task of image denoising.

• Type: Conference
• Year: 2008
• Where: ICIP
• Authors: Florent Ségonne, Nicolas Thorstensen, Renaud Keriven
• Keywords: Correct Normalization Criterion, Gaussian Kernel, ICIP 2008, Image Processing, Kernel PCA, Normalization Process