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6-DOF motion blur synthesis and performance evaluation of light field deblurring

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Abstract

Motion deblurring is essential for reconstructing sharp images from given a blurry input caused by the camera motion. The complexity of this problem increases in a light field due to its depth-dependent blur constraint. A method of generating synthetic 3 degree-of-freedom (3-DOF) translation blur on a light field image without camera rotation has been introduced. In this study, we generate a camera translation and rotation (6-DOF) motion blur model that preserves the consistency of the light field image. Our experiment results show that the proposed blur model can maintain the parallax information (depth-dependent blur) in a light field image. Furthermore, we produce a synthetic blurry light field dataset based on the 6-DOF model. Finally, to validate the usability of the synthetic dataset, we conduct extensive benchmarking using state-of-the-art motion deblurring algorithms.

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Acknowledgment

This work was supported by Inha University Research Grant.

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Authors and Affiliations

  1. Department Information and Communication Engineering, Inha University, Incheon, 22212, Korea

    Jonathan Samuel Lumentut & In Kyu Park

  2. Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta, 11480, Indonesia

    Williem

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  1. Jonathan Samuel Lumentut
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  2. Williem
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Correspondence to In Kyu Park.

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Lumentut, J.S., Williem & Park, I.K. 6-DOF motion blur synthesis and performance evaluation of light field deblurring. Multimed Tools Appl 78, 33723–33746 (2019). https://doi.org/10.1007/s11042-019-08030-0

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  • DOI: https://doi.org/10.1007/s11042-019-08030-0

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