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. © 2009 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Yang, P., Tong, X., Zheng, X., Zheng, J., & He, Y. (2009). A gradient-based adaptive interpolation filter for multiple view synthesis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5879 LNCS, pp. 551–560). https://doi.org/10.1007/978-3-642-10467-1_49
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