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Iterative Image Fusion Using Fuzzy Logic with Applications

  • Srinivasa Rao Dammavalam
  • Seetha Maddala
  • M. H. M. Krishna Prasad
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 177)

Abstract

Image fusion is the process of reducing uncertainty and minimizing redundancy while extracting all the useful information from the source images. Image fusion process is required for different applications like medical imaging, remote sensing, machine vision, biometrics and military applications. In this paper, an iterative fuzzy logic approach utilized to fuse images from different sensors, in order to enhance visualization. The proposed workfurther explores comparison between fuzzy based image fusion and iterative fuzzy fusion technique along with quality evaluation indices for image fusion like image quality index, mutual information measure, root mean square error, peak signal to noise ratio, entropy and correlation coefficient. Experimental results obtained from fusion process prove that the use of the proposed iterative fuzzy fusion can efficiently preserve the spectral information while improving the spatial resolution of the remote sensing images and medical imaging.

Keywords

image fusion panchromatic multispectral fuzzy logic image quality index mutual information measure entropy correlation coefficient 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Srinivasa Rao Dammavalam
    • 1
  • Seetha Maddala
    • 2
  • M. H. M. Krishna Prasad
    • 3
  1. 1.Department of Information TechnologyVNRVJIETHyderabadIndia
  2. 2.Department of CSEGNITSHyderabadIndia
  3. 3.Department of CSEJNTU College of EngineeringVizianagaramIndia

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