W-shaped selection for light field super-resolution

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Abstract

Commercial Light-Field cameras provide spatial and angular information, but its limited resolution becomes an important problem in practical use. Different from the conventional images, Light-Field images contain more information of different views that can be used for super-resolution and it makes super-resolution more credible. In this paper, we propose a interpolation based method for Light-Field image super-resolution by taking advantage of the epipolar plane image (EPI) to transfer angular information into spatial information. Firstly, we propose a color recovery framework for undetermined pixels. This framework contains three parts: we estimate the similar-color-diagonal (SCD) for known pixels, we construct a set of filters corresponding to different SCD to generate colors in order to provide a color selection set for undetermined pixel and we propose a W-shaped operator to select a more credible color for undetermined pixel. Finally we use this framework to interpolate EPI and the interpolated EPIs are used to reconstruct a high-resolution image. Experimental results demonstrate that the proposed method outperforms the state-of-art methods for Light-Field spatial super-resolution.

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Su, B., Sheng, H., Zhang, S., Yang, D., Chen, N., & Ke, W. (2018). W-shaped selection for light field super-resolution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11061 LNAI, pp. 148–159). Springer Verlag. https://doi.org/10.1007/978-3-319-99365-2_13

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