Implementation and Comparison of Image Fusion using Discrete Wavelet Transform and Principal Component Analysis

Authors

  • Vikas Kumar Mishra Computer Science and Engineering, Uttar Pradesh technical University, India
  • Shobhit Kumar Computer Science and Engineering, Uttar Pradesh technical University, India
  • Chandrabhan Singh Computer Science and Engineering, Uttar Pradesh technical University, India

Keywords:

Image Fusion, Wavelets, DWT,, PCA

Abstract

Nowadays with rapid development in high technology and modern instrumentation image fusion has become a vital component of a large number of applications. On the basis of three categories Pixel, Feature and decision a no of methods and algorithms have proposed for Image Fusion. This would be an interesting task to take some best recently used methods and analyze which one is better and effective. This Paper considers two fusion techniques Discrete Wavelet Transform (DWT) and Principal Component Analysis, fusion methods for these two techniques has been proposed and also the effectiveness is compared. In DWT the two images to be fused are decomposed at different levels and their approximation and detail co-efficient are calculated, a fusion scheme is used to combine these co-efficient and then Inverse of DWT is taken to reconstruct the image. In PCA the principal components of the two images are extracted and a fusion scheme is proposed to fuse these principal components to reconstruct the image. Finally comparison of these two techniques is performed on the basis of some evaluation criteria and the decision has drawn that which technique is better.

References

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Published

2014-03-31

How to Cite

[1]
V. K. Mishra, S. Kumar, and C. Singh, “Implementation and Comparison of Image Fusion using Discrete Wavelet Transform and Principal Component Analysis”, Int. J. Comp. Sci. Eng., vol. 2, no. 3, pp. 174–181, Mar. 2014.

Issue

Vol. 2 No. 3 (2014): IJCSE March Edition

Section

Research Article

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