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

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

doi:10.1109/ICIP.2019.8803728

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

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

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

3 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings
Publisher	IEEE Computer Society
Pages	774-778
Number of pages	5
ISBN (Electronic)	9781538662496
DOIs	https://doi.org/10.1109/ICIP.2019.8803728
Publication status	Published - 2019 Sept
Event	26th IEEE International Conference on Image Processing, ICIP 2019 - Taipei, Taiwan, Province of China Duration: 2019 Sept 22 → 2019 Sept 25

Publication series

Name	Proceedings - International Conference on Image Processing, ICIP
Volume	2019-September
ISSN (Print)	1522-4880

Conference

Conference	26th IEEE International Conference on Image Processing, ICIP 2019
Country/Territory	Taiwan, Province of China
City	Taipei
Period	19/9/22 → 19/9/25

Keywords

color gamut
convolutional neural network
gamut extension
image color analysis
image reconstruction

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

Access to Document

10.1109/ICIP.2019.8803728

Cite this

Takeuchi, M., Sakamoto, Y., Yokoyama, R., Sun, H., Matsuo, Y., & Katto, J. (2019). A Gamut-Extension Method Considering Color Information Restoration using Convolutional Neural Networks. In 2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings (pp. 774-778). [8803728] (Proceedings - International Conference on Image Processing, ICIP; Vol. 2019-September). IEEE Computer Society. https://doi.org/10.1109/ICIP.2019.8803728

A Gamut-Extension Method Considering Color Information Restoration using Convolutional Neural Networks. / Takeuchi, Masaru; Sakamoto, Yusuke; Yokoyama, Ryota et al.
2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings. IEEE Computer Society, 2019. p. 774-778 8803728 (Proceedings - International Conference on Image Processing, ICIP; Vol. 2019-September).

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

Takeuchi, M, Sakamoto, Y, Yokoyama, R, Sun, H, Matsuo, Y & Katto, J 2019, A Gamut-Extension Method Considering Color Information Restoration using Convolutional Neural Networks. in 2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings., 8803728, Proceedings - International Conference on Image Processing, ICIP, vol. 2019-September, IEEE Computer Society, pp. 774-778, 26th IEEE International Conference on Image Processing, ICIP 2019, Taipei, Taiwan, Province of China, 19/9/22. https://doi.org/10.1109/ICIP.2019.8803728

Takeuchi M, Sakamoto Y, Yokoyama R, Sun H, Matsuo Y, Katto J. A Gamut-Extension Method Considering Color Information Restoration using Convolutional Neural Networks. In 2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings. IEEE Computer Society. 2019. p. 774-778. 8803728. (Proceedings - International Conference on Image Processing, ICIP). doi: 10.1109/ICIP.2019.8803728

@inproceedings{f3eb315d55da468eb11341b17bb3aa1f,

title = "A Gamut-Extension Method Considering Color Information Restoration using Convolutional Neural Networks",

abstract = "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.",

keywords = "color gamut, convolutional neural network, gamut extension, image color analysis, image reconstruction",

author = "Masaru Takeuchi and Yusuke Sakamoto and Ryota Yokoyama and Heming Sun and Yasutaka Matsuo and Jiro Katto",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 26th IEEE International Conference on Image Processing, ICIP 2019 ; Conference date: 22-09-2019 Through 25-09-2019",

year = "2019",

month = sep,

doi = "10.1109/ICIP.2019.8803728",

language = "English",

series = "Proceedings - International Conference on Image Processing, ICIP",

publisher = "IEEE Computer Society",

pages = "774--778",

booktitle = "2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings",

}

TY - GEN

T1 - A Gamut-Extension Method Considering Color Information Restoration using Convolutional Neural Networks

AU - Takeuchi, Masaru

AU - Sakamoto, Yusuke

AU - Yokoyama, Ryota

AU - Sun, Heming

AU - Matsuo, Yasutaka

AU - Katto, Jiro

PY - 2019/9

Y1 - 2019/9

N2 - 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.

AB - 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.

KW - color gamut

KW - convolutional neural network

KW - gamut extension

KW - image color analysis

KW - image reconstruction

UR - http://www.scopus.com/inward/record.url?scp=85076800366&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85076800366&partnerID=8YFLogxK

U2 - 10.1109/ICIP.2019.8803728

DO - 10.1109/ICIP.2019.8803728

M3 - Conference contribution

AN - SCOPUS:85076800366

T3 - Proceedings - International Conference on Image Processing, ICIP

SP - 774

EP - 778

BT - 2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings

PB - IEEE Computer Society

T2 - 26th IEEE International Conference on Image Processing, ICIP 2019

Y2 - 22 September 2019 through 25 September 2019

ER -

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

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this