A Differential Evolutionary Multilevel Segmentation of Near Infra-Red Images Using Renyi’s Entropy

  • Soham Sarkar
  • Nayan Sen
  • Abhinava Kundu
  • Swagatam Das
  • Sheli Sinha Chaudhuri
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 199)

Abstract

In recent years remote sensing image processing has got some intense attention of the researchers for its utility in land cover study, natural calamity detection, object tracking etc. In case of remote sensing image processing, the primal objective is to sub divide the image into more than one segment. In doing so, Multi-level thresholding based image segmentation techniques play an useful role in accomplishing this critical task. Endeavor of this paper is to focus on obtaining the optimal multiple threshold points from a LISS III Near Infra-Red (NIR) band by employing Renyi’s Entropy. Moreover, a state-of-art meta-heuristics like Differential Evolution (DE) is incorporated to acquire optimal threshold values in reduced computational time with precision.

Keywords

Multilevel Image Segmentation Remote Sensing Images Renyi’s Entropy Differential Evolution LISS-III Near Infra-Red (NIR) 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Soham Sarkar
    • 1
  • Nayan Sen
    • 1
  • Abhinava Kundu
    • 1
  • Swagatam Das
    • 2
  • Sheli Sinha Chaudhuri
    • 3
  1. 1.Electronics and Communication Engineering DepartmentRCC Institute of Information TechnologyKolkataIndia
  2. 2.Electronics and Communication Sciences UnitIndian Statistical InstituteKolkataIndia
  3. 3.Electronics and Telecommunication Engineering DepartmentJadavpur UniversityKolkataIndia

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