Chapter 16. Remote Sensing Data Classification with Kernel Nonparametric Feature Extractions

  1. Dr Gustavo Camps-Valls B.Sc., Ph.D. professor member3 and
  2. Dr Lorenzo Bruzzone M.S., Ph.D. Postdoctoral Researcher Professor member Chair4
  1. Bor-Chen Kuo1,
  2. Jinn-Min Yang2 and
  3. Cheng-Hsuan Li1

Published Online: 4 NOV 2009

DOI: 10.1002/9780470748992.ch16

Kernel Methods for Remote Sensing Data Analysis

Kernel Methods for Remote Sensing Data Analysis

How to Cite

Kuo, B.-C., Yang, J.-M. and Li, C.-H. (2009) Remote Sensing Data Classification with Kernel Nonparametric Feature Extractions, in Kernel Methods for Remote Sensing Data Analysis (eds G. Camps-Valls and L. Bruzzone), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470748992.ch16

Editor Information

  1. 3

    Image Processing Laboratory (IPL) & Dept. Enginyeria Electrónica, Universitat de Valéncia, Spain

  2. 4

    Dept. Information Engineering and Computer Science, University of Trento, Italy

Author Information

  1. 1

    Graduate Institute of Educational Measurement and Statistics, National Taichung University, Taiwan

  2. 2

    Department of Mathematics Education, National Taichung University, Taiwan

Publication History

  1. Published Online: 4 NOV 2009
  2. Published Print: 23 OCT 2009

ISBN Information

Print ISBN: 9780470722114

Online ISBN: 9780470748992

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Keywords:

  • remote sensing data classification with kernel nonparametric feature extractions;
  • Nonparametric Weighted Feature Extraction (NWFE);
  • NWFE to Kernel-based NWFE (KNWFE);
  • Fuzzy Linear Feature Extraction (FLFE) and its Kernel-based version (KFFE);
  • Fisher's Linear Discriminant Analysis (LDA);
  • Fuzzy Linear Feature Extraction (FLFE);
  • kernel nonparametric feature extractions;
  • kernel-based fuzzy feature extraction (KFFE);
  • multiclass classification performances using ML;
  • kernel-based methods performance and choice of kernel functions

Summary

This chapter contains sections titled:

  • Introduction

  • Related feature extractions

  • Kernel-based NWFE and FLFE

  • Eigenvalue resolution with regularization

  • Experiments

  • Comments and conclusions

  • References