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Fast Computation of Image Scaling Algorithms Using Frequency Domain Approach

  • H. S. Prasantha
  • H. L. Shashidhara
  • K. N. B. Murthy
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 174)

Abstract

Image scaling algorithms play important role in many image scaling applications. Image scaling is the process of enlarging an image or reducing the size of an image to make it suitable to display on the given display device. The paper mainly focuses image zooming to fit the given image on a display device to view the details on a bigger display device. When the image is zoomed, artifacts like blurring, jagging and ghosting may arise. The main objective of the paper is to investigate and study the known algorithms for image scaling based on different comparative parameters in frequency domain. The different interpolation techniques such as nearest neighbor and bilinear are studied and compared in both spatial and frequency domain. The paper proposes a novel scheme for fast computation of the different image interpolation techniques.

Keywords

Mean Square Error Quality Index Fast Computation Bilinear Interpolation Frequency Domain Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Prasantha, H.S., Shashidhara, H.L., Balasubramanya Murthy, K.N.: Comparative analysis of different interpolation schemes in image processing. In: International Conference on Advanced Communication Systems (ICACS), India, pp. 17–24 (January 2007)Google Scholar
  2. 2.
    Prasantha, H.S., Shashidhara, H.L., Balasubramanya Murthy, K.N.: Image Scaling comparison using Universal Image Quality Index. In: International Conference on Advances in Computing, Control and Telecommunication Technologies (ICACCTT), India, pp. 859–863 (December 2009)Google Scholar
  3. 3.
    Gao, R., et al.: Image zooming algorithm based on partial differential equations technique. International Journal of Numerical Analysis and Modeling 6(2), 284–292Google Scholar
  4. 4.
    Matsuoka, R., et al.: Comparison of Image Interpolation Methods Applied to Least Squares Matching. In: CIMCA (2008)Google Scholar
  5. 5.
    Battiato, S., et al.: A locally adaptive zooming algorithm for digital images. Image and Vision Computing, 805–812 (2002)Google Scholar
  6. 6.
    Yuan, S., et al.: High accuracy WADI image interpolation with local gradient features. In: Proceedings of 2005 International Symposium on Intelligent Signal Processing and Communication System, Hongkong (2005)Google Scholar
  7. 7.
    Shi, Z., et al.: A novel nonlinear scaling method for video images. In: International Conference on Computer Science & Software Engineering, pp. 357–360.Google Scholar
  8. 8.
    Mihov, S.G., et al.: Interpolation algorithms for image scaling. Electronics (2005)Google Scholar
  9. 9.
    Lehmann, T.M., et al.: Survey: Interpolation Methods in Medical Image Processing. IEEE Transactions on Medical Imaging 18(11) (1999)Google Scholar
  10. 10.
    Acharya, T., et al.: Computational Foundations of image interpolation algorithms. ACM Ubiquity 8 (2007)Google Scholar
  11. 11.
    Wang, Z., et al.: A universal image quality Index. IEEE Signal Processing Letters XX(Y) (2002)Google Scholar

Copyright information

© Springer India 2013

Authors and Affiliations

  • H. S. Prasantha
    • 1
  • H. L. Shashidhara
    • 1
  • K. N. B. Murthy
    • 1
  1. 1.PES Institute of TechnologyBangaloreIndia

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