Enhanced Singular Value Decomposition based Fusion for Super Resolution Image Reconstruction

  • K. Joseph Abraham Sundar School of Computing, SASTRA University, Thanjavur
  • V. Vaithiyanathan School of Computing, SASTRA University, Thanjavur
  • M. Manickavasagam Defence Research and Development Laboratory, Hyderabad
  • A.K. Sarkar Defence Research and Development Laboratory, Hyderabad
Keywords: Singular value decomposition, image fusion, super resolution, image registration, interpolation

Abstract

The singular value decomposition (SVD) plays a very important role in the field of image processing for applications such as feature extraction, image compression, etc. The main objective is to enhance the resolution of the image based on Singular Value Decomposition. The original image and the subsequent sub-pixel shifted image, subjected to image registration is transferred to SVD domain. An enhanced method of choosing the singular values from the SVD domain images to reconstruct a high resolution image using fusion techniques is proposesed. This technique is called as enhanced SVD based fusion. Significant improvement in the performance is observed by applying enhanced SVD method preceding the various interpolation methods which are incorporated. The technique has high advantage and computationally fast which is most needed for satellite imaging, high definition television broadcasting, medical imaging diagnosis, military surveillance, remote sensing etc.

Published
2015-11-10
How to Cite
Sundar, K. J., Vaithiyanathan, V., Manickavasagam, M., & Sarkar, A. (2015). Enhanced Singular Value Decomposition based Fusion for Super Resolution Image Reconstruction. Defence Science Journal, 65(6), 459-465. https://doi.org/10.14429/dsj.65.8336
Section
Computers & Systems Studies

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