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Remote Sensing Image Classification: A Neuro-fuzzy MCS Approach

  • B. Uma Shankar
  • Saroj K. Meher
  • Ashish Ghosh
  • Lorenzo Bruzzone
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4338)

Abstract

The present article proposes a new neuro-fuzzy-fusion (NFF) method for combining the output of a set of fuzzy classifiers in a multiple classifier system (MCS) framework. In the proposed method the output of a set of classifiers (i.e., fuzzy class labels) are fed as input to a neural network, which performs the fusion task. The proposed fusion technique is tested on a set of remote sensing images and compared with existing techniques. Experimental study revealed the improved classification capability of the NFF based MCS as it yielded consistently better results.

Keywords

Fusion Method Speaker Recognition Remote Sensing Image Reasoning Rule Membership Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • B. Uma Shankar
    • 2
  • Saroj K. Meher
    • 2
  • Ashish Ghosh
    • 2
  • Lorenzo Bruzzone
    • 1
  1. 1.Department of Information and Communication TechnologiesUniversity of TrentoTrentoItaly
  2. 2.Machine Intelligence UnitIndian Statistical InstituteKolkataIndia

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