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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2025.2
- 수록면
- 55 - 64 (10page)
이용수
초록· 키워드
오류제보하기
As demand for high-resolution holographic displays in augmented and virtual reality (AR/VR) increases, the limitations of traditional computer-generated holography (CGH) upscaling methods, in- cluding bicubic interpolation and deep learning-based techniques, become apparent. These methods pre- dominantly estimate additional pixels without considering the reduction of pixel pitch, inherently con- straining their capacity to effectively expand the viewing angle. Our study introduces a novel approach for viewing angle expansion through light field (LF) extrapolation by applying an object detection algorithm. This process starts by analyzing the object position and depth information of each LF view extracted from CGH patterns with the object detection algorithm. The use of these data allows us to ex- trapolate LF views beyond their initial viewing angle limit. Subsequently, these expanded LF views are resynthesized into the CGH format to expand the viewing angle. With our approach, the viewing angle was successfully doubled from an initial 3.54 degrees to 7.09 degrees by upscaling a 2K 7.2 μm CGH to a 4K 3.6 μm CGH, which was verified with both numerical simulation and optical experiments.
목차
Ⅰ. INTRODUCTION
Ⅱ. DESIGN PRINCIPLE
Ⅲ. VERIFICATION
Ⅳ. CONCLUSION
REFERENCES
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