Using image texture analysis to improve land cover classification

  • Authors:

  • Xiaochen Zou;Daoliang Li

  • Affiliations:

  • College of Information and Electrical Engineering, China Agricultural University, Beijing, China and Key Laboratory of Modern Precision Agriculture System Integration, Ministry of Education, Beiji ...;College of Information and Electrical Engineering, China Agricultural University, Beijing, China and Key Laboratory of Modern Precision Agriculture System Integration, Ministry of Education, Beiji ...

  • Venue:
  • MATH'08 Proceedings of the 13th WSEAS international conference on Applied mathematics
  • Year:
  • 2008

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Abstract

Image texture analysis has received a considerable amount of attention over the last few years as it has played an important role in the classification of the remote sensing images. This paper provides an overview of several different approaches to image texture analysis and demonstrates their use on the problem of land cover classification. We used grey level co-occurrence matrix (GLCM) method to assistant the land cover classification and then compared and evaluated all of the result of classifications. In the experimentation, by comparing the classification result of contrast, energy and entropy we find out that the preferable texture features of grey level co-occurrence matrices method was contrast.