A Gamut-Extension Method Considering Color Information Restoration using Convolutional Neural Networks

Masaru Takeuchi, Yusuke Sakamoto, Ryota Yokoyama, Heming Sun, Yasutaka Matsuo, Jiro Katto

研究成果: Conference contribution

抄録

Recently, Ultra HDTV (UHDTV) services become popular over satellite and on the internet. On the contrary, there are tremendously huge volume of High Definition Television (HDTV) and Standard Definition Television (SDTV) contents stored in broadcasting companies and storage devices. In this paper, we propose a color space conversion (also known as gamut mapping) method from BT. 709 (used for current HDTV broadcast) to BT. 2020 (used for UHDTV broadcast), which estimates and restores lost color information. It learns an end-to-end conversion method from BT. 709 image to BT. 2020 image with restoring lost color information using Convolutional Neural Network (CNN). By experiments, we confirm that our method can achieve 2.31dB gain against the conventional method on average.

本文言語English
ホスト出版物のタイトル2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings
出版社IEEE Computer Society
ページ774-778
ページ数5
ISBN(電子版)9781538662496
DOI
出版ステータスPublished - 2019 9
イベント26th IEEE International Conference on Image Processing, ICIP 2019 - Taipei, Taiwan, Province of China
継続期間: 2019 9 222019 9 25

出版物シリーズ

名前Proceedings - International Conference on Image Processing, ICIP
2019-September
ISSN(印刷版)1522-4880

Conference

Conference26th IEEE International Conference on Image Processing, ICIP 2019
CountryTaiwan, Province of China
CityTaipei
Period19/9/2219/9/25

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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