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Performance Estimation of Generalized Statistical Smoothing to Inverse Halftoning Based on the MTF Function of Human Eyes

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Algorithms and Architectures for Parallel Processing (ICA3PP 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6082))

Abstract

We construct a method of the generalized statistical smoothing (GSS) to the problem of inverse halftoning for a halftone image which is converted by the error diffusion method. Especially, we construct the present method so as to achieve the optimal performance on the basis of the mean square error (MSE) between original and restored images both of which are observed through the MTF function of human vision system. Using the numerical simulation for several 256-level standard images, we clarify that the optimal performance of the GSS is realized if we appropriately set the parameters controlling both edge enhancement procedure and generalized parameter scheduling. We also find the GSS restores the original image more accurately than other conventional filters, such as the average and Gaussian filters.

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References

  1. Ulichney, R.: Digital Halftoning. The MIT Press, Cambridge (1987)

    Google Scholar 

  2. Bayer, B.E.: An optimum method for two-level rendition of continuous-tone pictures. In: ICC Conf. Record, pp. 11–15 (1973)

    Google Scholar 

  3. Floyd, R.W., Steinburg, L.: Adaptive algorithm for spatial gray scale. In: SID Int. Sym. Digest of Tech. Papers, pp. 36–37 (1975)

    Google Scholar 

  4. Miceli, C.M., Parker, K.J.: Inverse halftoning. J. Electron Imaging 1, 143–151 (1992)

    Article  Google Scholar 

  5. Stevenson, R.: Inverse halftoning via MAP estimation. IEEE Trans. Image Processing 6, 574–583 (1995)

    Article  Google Scholar 

  6. Saika, Y., Inoue, I.: Probabilistic inference to the problem of inverse-halftoning based on statistical mechanics of spin systems, Probabilistic inference to the problem of inverse-halftoning based on statistical mechanics of spin systems. In: Proceeding of the. SICE-ICCAS2006, pp. 4563–4568 (2006)

    Google Scholar 

  7. Saika, Y., Inoue, J., Tanaka, H., Okada, M.: Bayes-optimal solution to inverse halftoning. Central European Journal of Physics, 444–456 (2009)

    Google Scholar 

  8. Wong, P.W.: Inverse Halftoning and Kernel Estimation for Error Diffusion. IEEE Trans. Image Processing 4, 486–498 (1995)

    Article  Google Scholar 

  9. Saika, Y., Yamasaki, T.: Generalized Statistical Smoothing to the Problem of Inverse Halftoning for Error Diffusion. In: The Proceeding of the ICCAS 2007, pp. 781–784 (2007)

    Google Scholar 

  10. Dooley, R.P., Shaw, R.: Noise Reduction Perception in Electrography. J. Appl. Photogr. Eng. 5(4), 190–196 (1979)

    Google Scholar 

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Wakayama National College of, Technology, Nada Noshima 77, Gobo, Wakayama, 644-0023, Japan

    Yohei Saika & Kouki Sugimoto

  2. Department of Advanced Engineering, Wakayama National College of Technology, Nada Noshima 77, Gobo, Wakayama, 644-0023, Japan

    Yohei Saika & Ken Okamoto

Authors
  1. Yohei Saika
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  2. Kouki Sugimoto
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  3. Ken Okamoto
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Information Engineering, Chung Hua University, 300, Hsinchu, Taiwan, China

    Ching-Hsien Hsu

  2. Department of Computer Science, St. Francis Xavier University, B2G 2W5, Antigonish, NS, Canada

    Laurence T. Yang

  3. Department of Computer Science ad Engineering, Seoul National University of Technology, 172 Gongreund 2-dong, Nowon-gou, 139-742, Seoul, Korea

    Jong Hyuk Park

  4. Division of Computer Engineering, Mokwon University, 302-729, Daejeon, Korea

    Sang-Soo Yeo

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© 2010 Springer-Verlag Berlin Heidelberg

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Saika, Y., Sugimoto, K., Okamoto, K. (2010). Performance Estimation of Generalized Statistical Smoothing to Inverse Halftoning Based on the MTF Function of Human Eyes. In: Hsu, CH., Yang, L.T., Park, J.H., Yeo, SS. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2010. Lecture Notes in Computer Science, vol 6082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13136-3_37

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  • DOI: https://doi.org/10.1007/978-3-642-13136-3_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13135-6

  • Online ISBN: 978-3-642-13136-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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