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Image Resize Application of Novel Stochastic Methods of Function Recovery

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Advances in Hybrid Information Technology (ICHIT 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4413))

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Abstract

A novel family of stochastic methods developed for function recovery tasks is presented and its properties are discussed in some detail. A new image resize facility based on these new methods is applied to an image and this compares favorably in quality to the application to this image of an equivalent facility from a popular commercial graphics package.

This work was carried out as part of the Electronic Systems Domain of the Ministry of Defence Research Programme.

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References

  1. Method and apparatus for approximating, deconvolving and interpolating data using Berstein functions. U.S. Provisional Patent Application No. 60544,975 #20050203982  (2004)

    Google Scholar 

  2. Howard, D., Kolibal, J.: Solution of differential equations with genetic programming and the stochastic bernstein interpolation. In: Biocoumputing-Developmental Systems Group, University of Limerick Technical Report No. BDS-TR-2005-001. University of Limerick, Limerick, Ireland (June 2005), http://www.genetic-programming.org/hc2005/bds.pdf

  3. Howard, D., Roberts, S.C.: Genetic programming solution of the convection-diffusion equation. In: Spector, L., Goodman, E.D., Wu, A., Langdon, W.B., Voigt, H.-M., Gen, M., Sen, S., Dorigo, M., Pezeshk, S., Garzon, M.H., Burke, E. (eds.) Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), 7–11 July 2001, pp. 34–41. Morgan Kaufmann, San Francisco, California, USA (2001)

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  4. Kolibal, J., Howard, D.: Maldi-tof baseline drift removal using stochastic Bernstein approximation. EURASIP Journal on Applied Signal Processing, Special Issue on Advanced Signal Processing Techniques for Bioinformatics 2006, 1–9 (2006)

    Google Scholar 

  5. Kolibal, J., Saltiel, C.: Data regularization using stochastic methods. Submitted to SIAM  (2005)

    Google Scholar 

  6. Kolibal, J., Howard, D.: The novel stochastic Bernstein method of functional approximation. In: Adaptive Hardware and Systems, 2006. AHS 2006. First NASA/ESA Conference on, Istanbul, Turkey, 15–18 June 2006, pp. 97–100. IEEE Computer Society Press, Los Alamitos (2006)

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  7. Seyfarth, R., Kolibal, J., Howard, D.: New mathematical method for computer graphics. In: Proceedings of 2006 International Conference on Hybrid Information Technology (ICHIT 2006), 11–13 November 2006, pp. 8–12. IEEE Computer Society Press, Los Alamitos (2006)

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Authors

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Marcin S. Szczuka Daniel Howard Dominik Ślȩzak Haeng-kon Kim Tai-hoon Kim Il-seok Ko Geuk Lee Peter M. A. Sloot

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© 2007 Springer-Verlag Berlin Heidelberg

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Howard, D., Kolibal, J. (2007). Image Resize Application of Novel Stochastic Methods of Function Recovery. In: Szczuka, M.S., et al. Advances in Hybrid Information Technology. ICHIT 2006. Lecture Notes in Computer Science(), vol 4413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77368-9_12

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  • DOI: https://doi.org/10.1007/978-3-540-77368-9_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77367-2

  • Online ISBN: 978-3-540-77368-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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