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A Gradient-Based Adaptive Interpolation Filter for Multiple View Synthesis

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Advances in Multimedia Information Processing - PCM 2009 (PCM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5879))

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Abstract

A gradient-based adaptive interpolation method is proposed in this paper to solve the over-blurring problem in conventional multiple view synthesis (MVS) filters. To improve the visual quality of final synthetic pictures, a good interpolation filter is required in multiple view synthesis steps. Traditional space-invariant filters, such as bi-linear or bi-cubic filter, take the advantage of complexity, but they also lead to a decrease of the subjective quality. In contrast, directional filters usually exploit the directional information, especially in edge area, to deal with the over-blurring problem. This paper proposes a fast directional interpolation method for scaling up the resolution or filling up the losing pixels of a picture. The gradient map of an input picture is calculated in first. Using the gradient of each input pixel, the interpolation coefficients computed from a Gaussian kernel is refined, leading to a directional filter which takes an adaptation with gradient direction. This method is with a low complexity because it is a non-iterative method, and experiment results show that the visual quality of interpolated picture is improved.

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© 2009 Springer-Verlag Berlin Heidelberg

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Yang, P., Tong, X., Zheng, X., Zheng, J., He, Y. (2009). A Gradient-Based Adaptive Interpolation Filter for Multiple View Synthesis. In: Muneesawang, P., Wu, F., Kumazawa, I., Roeksabutr, A., Liao, M., Tang, X. (eds) Advances in Multimedia Information Processing - PCM 2009. PCM 2009. Lecture Notes in Computer Science, vol 5879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10467-1_49

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  • DOI: https://doi.org/10.1007/978-3-642-10467-1_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10466-4

  • Online ISBN: 978-3-642-10467-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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