Nonlinear discriminant analysis

Research output: Contribution to journalArticle

Abstract

We describe a new nonlinear discriminant analysis method for feature extraction. This method applies a nonsingular transform to the data such that the transformed data have a Gaussian distribution. Then a Bayes likelihood ratio is calculated for the transformed data. The nonsingular transform makes use of wavelet transforms and histogram matching. Wavelet transforms are an effective tool in analyzing data structures. Histogram matching is applied to the wavelet coefficients and the ordinary image pixel values in order to create a transformed image that has the desired Gaussian statistics.

Original languageEnglish (US)
Pages (from-to)448-455
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4322
Issue number1
DOIs
StatePublished - Jul 3 2001

Keywords

  • Histogram matching
  • Hypothesis testing
  • Nonlinear discriminant analysis
  • Nonsingular transform
  • Wavelets

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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