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6-DOF motion blur synthesis and performance evaluation of light field deblurring
- Lumentut, Jonathan Samuel;
- Williem;
- Park, In Kyu
WEB OF SCIENCE
2SCOPUS
3초록
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.
키워드
- 제목
- 6-DOF motion blur synthesis and performance evaluation of light field deblurring
- 저자
- Lumentut, Jonathan Samuel; Williem; Park, In Kyu
- 발행일
- 2019-12
- 유형
- Article
- 권
- 78
- 호
- 23
- 페이지
- 33723 ~ 33746