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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.10
- 수록면
- 524 - 531 (8page)
이용수
초록· 키워드
오류제보하기
In an integral-imaging microscopy (IIM) system, a microlens array (MLA) is the primary optical element; however, surface errors impede the resolution of a raw image’s details. Calibration is a major concern with regard to incorrect projection of the light rays. A ray-tracing-based calibration method for an IIM camera is proposed, to address four errors: MLA decentering, rotational, translational, and subimage-scaling errors. All of these parameters are evaluated using the reference image obtained from the ray-traced white image. The areas and center points of the microlens are estimated using an “8-connected” and a “center-of-gravity” method respectively. The proposed approach significantly improves the rectified-image quality and nonlinear image brightness for an IIM system. Numerical and optical experiments on multiple real objects demonstrate the robustness and effectiveness of our proposed method, which achieves on average a 35% improvement in brightness for an IIM raw image.
목차
Ⅰ. INTRODUCTION
Ⅱ. MODELS AND METHODS
Ⅲ. PROPOSED METHOD
Ⅳ. RESULTS
Ⅴ. CONCLUSION
REFERENCES
참고문헌 (27)
참고문헌 신청
M. Levoy / 2006 / Light fields and computational imaging / Computer 39:46~55
K.-C. Kwon / 2019 / Resolution-enhancement for an integral imaging microscopy using deep learning / IEEE Photonics J 11:6900512
M. S. Alam / 2021 / Super-resolution enhancement method based on generative adversarial network for integral imaging microscopy / Sensors 21:2164
M. Y. Abbass / 2021 / Image super resolution based on residual dense CNN and guided filters / Multimed. Tools Appl 80:5403~5421
K. -C. Kwon / 2016 / Integral imaging microscopy with enhanced depth-of-field using a spatial multiplexing / Opt. Express 24:2072~2083
K.-C. Kwon / 2019 / Resolution-enhancement for an integral imaging microscopy using deep learning / IEEE Photonics J 11:6900512
M. S. Alam / 2021 / Super-resolution enhancement method based on generative adversarial network for integral imaging microscopy / Sensors 21:2164
M. Y. Abbass / 2021 / Image super resolution based on residual dense CNN and guided filters / Multimed. Tools Appl 80:5403~5421
K. -C. Kwon / 2016 / Integral imaging microscopy with enhanced depth-of-field using a spatial multiplexing / Opt. Express 24:2072~2083
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