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Conference Papers Year : 2008

Normalization and preimage problem in gaussian kernel PCA

Abstract

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.
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Dates and versions

hal-00835106 , version 1 (18-06-2013)

Identifiers

  • HAL Id : hal-00835106 , version 1

Cite

Nicolas Thorstensen, Florent Ségonne, Renaud Keriven. Normalization and preimage problem in gaussian kernel PCA. ICIP, Oct 2008, San Diego, United States. pp.741-744. ⟨hal-00835106⟩
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