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Enhancing Robustness of Embedded Medical Images with a 4 level Contourlet Transform

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  • J. Samuel Manoharan
  • G. Jayaseelan
  • P. Muralidharan

Abstract

Medical Images are an important class in the sense that they deal with real time conditions and are highly sensitive. Any slightest modification or manipulations done during their processing could degrade the quality of the image which could severely affect the efficiency of embedding techniques. Hence, Robustness and Fidelity are two important criteria that need to be adhered to in any data embedding technique. A multi resolution approximation technique using the Contourlet transform has been introduced in this paper and its effectiveness towards a wide range of aggressive image processing operations simulating the real time attacks has been found to make it a suitable transform to embed data into sensitiveness prone medical images. The results have been expressed in terms of well known metrics like PSNR, Correlation Coefficient and the structural similarity index.

Suggested Citation

  • J. Samuel Manoharan & G. Jayaseelan & P. Muralidharan, 2016. "Enhancing Robustness of Embedded Medical Images with a 4 level Contourlet Transform," International Journal of Scientific Research in Science, Engineering and Technology, International Journal of Scientific Research in Science, Engineering and Technology, vol. 2(6), pages 149-154, December.
    • Handle: RePEc:ijs:ijsrse:v2:y2016:i6:id:hijsrset162643
    Note: Article URL: https://ijsrset.com/IJSRSET162643
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