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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.9 No.4
- 발행연도
- 2020.8
- 수록면
- 312 - 316 (5page)
- DOI
- 10.5573/IEIESPC.2020.9.4.312
이용수
초록· 키워드
오류제보하기
The resolution, intensity range and color gamut of the latest display devices such as organic light-emitting diode (OLED) displays have been improved significantly compared to conventional display devices. Regarding the intensity range, the latest display devices can produce a maximum luminous intensity of 1,000 nits or more, which extends the intensity range considerably compared to conventional displays, which have a maximum luminous intensity of approximately 300 nits. In this paper, a deep learning-based image intensity range extension method is studied. The input and target images for deep learning are generated from the high dynamic range (HDR) images, and the target images have an extended intensity range using the Hybrid Log-Gamma (HLG) curve. A modified structure of U-net is proposed to improve the convergence of U-net, and an efficient learning method through the adoption of a structural similarity (SSIM) loss as a loss function is also proposed. The extensive simulations reveal the significantly improved performance of the proposed method.
목차
Abstract
1. Introduction
2. Extension of Image Intensity Using Hybrid Log-Gamma
3. Proposed Deep Learning Method for Extending the Image Intensity
4. Performance Evaluation
5. Conclusion
References
참고문헌 (18)
참고문헌 신청
Y. Nagata / 2017 / Content production technology on Hybrid Log-Gamma / Proc. of SMPTE 2017 Annual Technical Conference and Exhibition
Y. Xu / 2019 / Gan based multi-exposure inverse tone mapping / Proc. of IEEE International Conference on Image Processing (ICIP) 2019 :22~25
G. Eilertsen / 2017 / HDR image reconstruction from a single exposure using deep CNNs / ACM Transactions on Graphics 36(6)
X. Hou / 2017 / Image companding and inverse halftoning using deep convolutional neural networks / arXiv:1707.00116
Keunsoo Heo / 2019 / Efficient Deep Neural Network for Restoring Image Intensity / IEIE Transactions on Smart Processing & Computing 8(2):121~125
Y. Xu / 2019 / Gan based multi-exposure inverse tone mapping / Proc. of IEEE International Conference on Image Processing (ICIP) 2019 :22~25
G. Eilertsen / 2017 / HDR image reconstruction from a single exposure using deep CNNs / ACM Transactions on Graphics 36(6)
X. Hou / 2017 / Image companding and inverse halftoning using deep convolutional neural networks / arXiv:1707.00116
Keunsoo Heo / 2019 / Efficient Deep Neural Network for Restoring Image Intensity / IEIE Transactions on Smart Processing & Computing 8(2):121~125
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UCI(KEPA) : I410-ECN-0101-2020-569-001078660