Fast multistage Gaussian maximum likelihood classifier

Chulhee Lee, David A. Landgrebe

Research output: Contribution to conferencePaper

Abstract

The authors propose a multistage classification algorithm based on the Gaussian maximum-likelihood (ML) procedure. A discriminant function is calculated for classes at each stage, and the classes whose discriminant function values are less than a threshold are truncated. The algorithm reduces processing time substantially without losing any significant accuracy. The computing time can be reduced by a factor of 3-7 using the proposed multistage classifiers when the Gaussian ML classifier is to be used. Therefore, after features which depend on an accuracy requirement have been selected, the processing time can be reduced substantially without losing any significant accuracy by employing the multistage classifiers.

Original languageEnglish
Pages349-352
Number of pages4
Publication statusPublished - 1990 Dec 1
Event10th Annual International Geoscience and Remote Sensing Symposium - IGARSS '90 - College Park, MD, USA
Duration: 1990 May 201990 May 20

Other

Other10th Annual International Geoscience and Remote Sensing Symposium - IGARSS '90
CityCollege Park, MD, USA
Period90/5/2090/5/20

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All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

Cite this

Lee, C., & Landgrebe, D. A. (1990). Fast multistage Gaussian maximum likelihood classifier. 349-352. Paper presented at 10th Annual International Geoscience and Remote Sensing Symposium - IGARSS '90, College Park, MD, USA, .