Convolutional Neural Network based Inverse Tone Mapping for High Dynamic Range Display using LUCORE

Katsuhiko Hirao; Zhengxue Cheng; Masaru Takeuchi; Jiro Katto

doi:10.1109/ICCE.2019.8662048

Convolutional Neural Network based Inverse Tone Mapping for High Dynamic Range Display using LUCORE

Katsuhiko Hirao, Zhengxue Cheng, Masaru Takeuchi, Jiro Katto

School of Fundamental Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

The popularity of high dynamic range (HDR) makes the inverse tone mapping become an important technique for HDR display. In this paper, we propose a convolutional neural network (CNN)-based inverse tone mapping method to generate a high-quality HDR image from one single standard dynamic range (SDR) image. First, we present a CNN design with a three- channel input, which considers both luminance and chrominance. Second, we propose to use overlapped inputs to remove the boundary artifacts, caused by zero paddings in CNN. Experimental results demonstrate the high quality of our generated HDR images compared to the ground truth.

Original language	English
Title of host publication	2019 IEEE International Conference on Consumer Electronics, ICCE 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538679104
DOIs	https://doi.org/10.1109/ICCE.2019.8662048
Publication status	Published - 2019 Mar 6
Event	2019 IEEE International Conference on Consumer Electronics, ICCE 2019 - Las Vegas, United States Duration: 2019 Jan 11 → 2019 Jan 13

Publication series

Name	2019 IEEE International Conference on Consumer Electronics, ICCE 2019

Conference

Conference	2019 IEEE International Conference on Consumer Electronics, ICCE 2019
Country/Territory	United States
City	Las Vegas
Period	19/1/11 → 19/1/13

ASJC Scopus subject areas

Industrial and Manufacturing Engineering
Media Technology
Electrical and Electronic Engineering

Access to Document

10.1109/ICCE.2019.8662048

Cite this

Hirao, K., Cheng, Z., Takeuchi, M., & Katto, J. (2019). Convolutional Neural Network based Inverse Tone Mapping for High Dynamic Range Display using LUCORE. In 2019 IEEE International Conference on Consumer Electronics, ICCE 2019 [8662048] (2019 IEEE International Conference on Consumer Electronics, ICCE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE.2019.8662048

Convolutional Neural Network based Inverse Tone Mapping for High Dynamic Range Display using LUCORE. / Hirao, Katsuhiko; Cheng, Zhengxue; Takeuchi, Masaru et al.
2019 IEEE International Conference on Consumer Electronics, ICCE 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8662048 (2019 IEEE International Conference on Consumer Electronics, ICCE 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hirao, K, Cheng, Z, Takeuchi, M & Katto, J 2019, Convolutional Neural Network based Inverse Tone Mapping for High Dynamic Range Display using LUCORE. in 2019 IEEE International Conference on Consumer Electronics, ICCE 2019., 8662048, 2019 IEEE International Conference on Consumer Electronics, ICCE 2019, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Conference on Consumer Electronics, ICCE 2019, Las Vegas, United States, 19/1/11. https://doi.org/10.1109/ICCE.2019.8662048

Hirao K, Cheng Z, Takeuchi M, Katto J. Convolutional Neural Network based Inverse Tone Mapping for High Dynamic Range Display using LUCORE. In 2019 IEEE International Conference on Consumer Electronics, ICCE 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8662048. (2019 IEEE International Conference on Consumer Electronics, ICCE 2019). doi: 10.1109/ICCE.2019.8662048

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abstract = "The popularity of high dynamic range (HDR) makes the inverse tone mapping become an important technique for HDR display. In this paper, we propose a convolutional neural network (CNN)-based inverse tone mapping method to generate a high-quality HDR image from one single standard dynamic range (SDR) image. First, we present a CNN design with a three- channel input, which considers both luminance and chrominance. Second, we propose to use overlapped inputs to remove the boundary artifacts, caused by zero paddings in CNN. Experimental results demonstrate the high quality of our generated HDR images compared to the ground truth.",

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AB - The popularity of high dynamic range (HDR) makes the inverse tone mapping become an important technique for HDR display. In this paper, we propose a convolutional neural network (CNN)-based inverse tone mapping method to generate a high-quality HDR image from one single standard dynamic range (SDR) image. First, we present a CNN design with a three- channel input, which considers both luminance and chrominance. Second, we propose to use overlapped inputs to remove the boundary artifacts, caused by zero paddings in CNN. Experimental results demonstrate the high quality of our generated HDR images compared to the ground truth.

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Convolutional Neural Network based Inverse Tone Mapping for High Dynamic Range Display using LUCORE

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