Wide Color Gamut Image Content Characterization: Method, Evaluation, and Applications

In this paper, we propose a novel framework to characterize a wide color gamut image content based on perceived quality due to the processes that change color gamut, and demonstrate two practical use cases where the framework can be applied. We first introduce the main framework and implementation d...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on multimedia 2021, Vol.23, p.3817-3827
Main Authors: Lee, Junghyuk, Vigier, Toinon, Le Callet, Patrick, Lee, Jong-Seok
Format: Article
Language:English
Subjects:
Color
color gamut mapping
Computer Science
content characterization
content selection
Criteria
Image color analysis
Image Processing
Image quality
Measurement
Multimedia
Quality of experience
Reliability analysis
Toy manufacturing industry
Visualization
Wide color gamut
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c367t-b62a6e8ab7736c13ff54d6882f550354c28ed18ea6274a26e00a2e8aa1bbc2b73
cites cdi_FETCH-LOGICAL-c367t-b62a6e8ab7736c13ff54d6882f550354c28ed18ea6274a26e00a2e8aa1bbc2b73
container_end_page 3827
container_issue
container_start_page 3817
container_title IEEE transactions on multimedia
container_volume 23
creator Lee, Junghyuk
Vigier, Toinon
Le Callet, Patrick
Lee, Jong-Seok
description In this paper, we propose a novel framework to characterize a wide color gamut image content based on perceived quality due to the processes that change color gamut, and demonstrate two practical use cases where the framework can be applied. We first introduce the main framework and implementation details. Then, we provide analysis for understanding of existing wide color gamut datasets with quantitative characterization criteria on their characteristics, where four criteria, i.e., coverage, total coverage, uniformity, and total uniformity, are proposed. Finally, the framework is applied to content selection in a gamut mapping evaluation scenario in order to enhance reliability and robustness of the evaluation results. As a result, the framework fulfils content characterization for studies where quality of experience of wide color gamut stimuli is involved.
doi_str_mv 10.1109/TMM.2020.3032026
format article
fullrecord <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_03205745v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9234679</ieee_id><sourcerecordid>2583636674</sourcerecordid><originalsourceid>FETCH-LOGICAL-c367t-b62a6e8ab7736c13ff54d6882f550354c28ed18ea6274a26e00a2e8aa1bbc2b73</originalsourceid><addsrcrecordid>eNo9kEFLw0AQRhdRsFbvgpeAJ6Gps7vZ3cRbCbUttHhp8bhMko1NSZO4SQr6601M6WmGj_cNwyPkkcKUUghet5vNlAGDKQfeTXlFRjTwqAug1HW3CwZuwCjckru6PgBQT4Aakd1nlhgnLPPSOgs8to2zOuJXnxSNKRon3KPFuDE2-8UmK4s3Z2OafZlMnPkJ8_Y_mzhYJM6sqvIs_g_qe3KTYl6bh_Mck937fBsu3fXHYhXO1m7MpWrcSDKUxsdIKS5jytNUeIn0fZYKAVx4MfNNQn2DkikPmTQAyDoeaRTFLFJ8TF6Gu3vMdWWzI9ofXWKml7O17rPehVCeONGOfR7YypbfrakbfShbW3TvaSZ8LrmUyusoGKjYlnVtTXo5S0H3onUnWvei9Vl0V3kaKpkx5oIHjHtSBfwPo_53tw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2583636674</pqid></control><display><type>article</type><title>Wide Color Gamut Image Content Characterization: Method, Evaluation, and Applications</title><source>IEEE Xplore (Online service)</source><creator>Lee, Junghyuk ; Vigier, Toinon ; Le Callet, Patrick ; Lee, Jong-Seok</creator><creatorcontrib>Lee, Junghyuk ; Vigier, Toinon ; Le Callet, Patrick ; Lee, Jong-Seok</creatorcontrib><description>In this paper, we propose a novel framework to characterize a wide color gamut image content based on perceived quality due to the processes that change color gamut, and demonstrate two practical use cases where the framework can be applied. We first introduce the main framework and implementation details. Then, we provide analysis for understanding of existing wide color gamut datasets with quantitative characterization criteria on their characteristics, where four criteria, i.e., coverage, total coverage, uniformity, and total uniformity, are proposed. Finally, the framework is applied to content selection in a gamut mapping evaluation scenario in order to enhance reliability and robustness of the evaluation results. As a result, the framework fulfils content characterization for studies where quality of experience of wide color gamut stimuli is involved.</description><identifier>ISSN: 1520-9210</identifier><identifier>EISSN: 1941-0077</identifier><identifier>DOI: 10.1109/TMM.2020.3032026</identifier><identifier>CODEN: ITMUF8</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Color ; color gamut mapping ; Computer Science ; content characterization ; content selection ; Criteria ; Image color analysis ; Image Processing ; Image quality ; Measurement ; Multimedia ; Quality of experience ; Reliability analysis ; Toy manufacturing industry ; Visualization ; Wide color gamut</subject><ispartof>IEEE transactions on multimedia, 2021, Vol.23, p.3817-3827</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c367t-b62a6e8ab7736c13ff54d6882f550354c28ed18ea6274a26e00a2e8aa1bbc2b73</citedby><cites>FETCH-LOGICAL-c367t-b62a6e8ab7736c13ff54d6882f550354c28ed18ea6274a26e00a2e8aa1bbc2b73</cites><orcidid>0000-0002-6164-0728 ; 0000-0002-8038-1119 ; 0000-0002-2143-7063 ; 0000-0002-3193-4020</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9234679$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,314,776,780,881,4009,27902,27903,27904,54775</link.rule.ids><backlink>$$Uhttps://hal.science/hal-03205745$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Lee, Junghyuk</creatorcontrib><creatorcontrib>Vigier, Toinon</creatorcontrib><creatorcontrib>Le Callet, Patrick</creatorcontrib><creatorcontrib>Lee, Jong-Seok</creatorcontrib><title>Wide Color Gamut Image Content Characterization: Method, Evaluation, and Applications</title><title>IEEE transactions on multimedia</title><addtitle>TMM</addtitle><description>In this paper, we propose a novel framework to characterize a wide color gamut image content based on perceived quality due to the processes that change color gamut, and demonstrate two practical use cases where the framework can be applied. We first introduce the main framework and implementation details. Then, we provide analysis for understanding of existing wide color gamut datasets with quantitative characterization criteria on their characteristics, where four criteria, i.e., coverage, total coverage, uniformity, and total uniformity, are proposed. Finally, the framework is applied to content selection in a gamut mapping evaluation scenario in order to enhance reliability and robustness of the evaluation results. As a result, the framework fulfils content characterization for studies where quality of experience of wide color gamut stimuli is involved.</description><subject>Color</subject><subject>color gamut mapping</subject><subject>Computer Science</subject><subject>content characterization</subject><subject>content selection</subject><subject>Criteria</subject><subject>Image color analysis</subject><subject>Image Processing</subject><subject>Image quality</subject><subject>Measurement</subject><subject>Multimedia</subject><subject>Quality of experience</subject><subject>Reliability analysis</subject><subject>Toy manufacturing industry</subject><subject>Visualization</subject><subject>Wide color gamut</subject><issn>1520-9210</issn><issn>1941-0077</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNo9kEFLw0AQRhdRsFbvgpeAJ6Gps7vZ3cRbCbUttHhp8bhMko1NSZO4SQr6601M6WmGj_cNwyPkkcKUUghet5vNlAGDKQfeTXlFRjTwqAug1HW3CwZuwCjckru6PgBQT4Aakd1nlhgnLPPSOgs8to2zOuJXnxSNKRon3KPFuDE2-8UmK4s3Z2OafZlMnPkJ8_Y_mzhYJM6sqvIs_g_qe3KTYl6bh_Mck937fBsu3fXHYhXO1m7MpWrcSDKUxsdIKS5jytNUeIn0fZYKAVx4MfNNQn2DkikPmTQAyDoeaRTFLFJ8TF6Gu3vMdWWzI9ofXWKml7O17rPehVCeONGOfR7YypbfrakbfShbW3TvaSZ8LrmUyusoGKjYlnVtTXo5S0H3onUnWvei9Vl0V3kaKpkx5oIHjHtSBfwPo_53tw</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Lee, Junghyuk</creator><creator>Vigier, Toinon</creator><creator>Le Callet, Patrick</creator><creator>Lee, Jong-Seok</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><general>Institute of Electrical and Electronics Engineers</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-6164-0728</orcidid><orcidid>https://orcid.org/0000-0002-8038-1119</orcidid><orcidid>https://orcid.org/0000-0002-2143-7063</orcidid><orcidid>https://orcid.org/0000-0002-3193-4020</orcidid></search><sort><creationdate>2021</creationdate><title>Wide Color Gamut Image Content Characterization: Method, Evaluation, and Applications</title><author>Lee, Junghyuk ; Vigier, Toinon ; Le Callet, Patrick ; Lee, Jong-Seok</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c367t-b62a6e8ab7736c13ff54d6882f550354c28ed18ea6274a26e00a2e8aa1bbc2b73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Color</topic><topic>color gamut mapping</topic><topic>Computer Science</topic><topic>content characterization</topic><topic>content selection</topic><topic>Criteria</topic><topic>Image color analysis</topic><topic>Image Processing</topic><topic>Image quality</topic><topic>Measurement</topic><topic>Multimedia</topic><topic>Quality of experience</topic><topic>Reliability analysis</topic><topic>Toy manufacturing industry</topic><topic>Visualization</topic><topic>Wide color gamut</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Junghyuk</creatorcontrib><creatorcontrib>Vigier, Toinon</creatorcontrib><creatorcontrib>Le Callet, Patrick</creatorcontrib><creatorcontrib>Lee, Jong-Seok</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) Online</collection><collection>IEEE Xplore (Online service)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>IEEE transactions on multimedia</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Junghyuk</au><au>Vigier, Toinon</au><au>Le Callet, Patrick</au><au>Lee, Jong-Seok</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Wide Color Gamut Image Content Characterization: Method, Evaluation, and Applications</atitle><jtitle>IEEE transactions on multimedia</jtitle><stitle>TMM</stitle><date>2021</date><risdate>2021</risdate><volume>23</volume><spage>3817</spage><epage>3827</epage><pages>3817-3827</pages><issn>1520-9210</issn><eissn>1941-0077</eissn><coden>ITMUF8</coden><abstract>In this paper, we propose a novel framework to characterize a wide color gamut image content based on perceived quality due to the processes that change color gamut, and demonstrate two practical use cases where the framework can be applied. We first introduce the main framework and implementation details. Then, we provide analysis for understanding of existing wide color gamut datasets with quantitative characterization criteria on their characteristics, where four criteria, i.e., coverage, total coverage, uniformity, and total uniformity, are proposed. Finally, the framework is applied to content selection in a gamut mapping evaluation scenario in order to enhance reliability and robustness of the evaluation results. As a result, the framework fulfils content characterization for studies where quality of experience of wide color gamut stimuli is involved.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/TMM.2020.3032026</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-6164-0728</orcidid><orcidid>https://orcid.org/0000-0002-8038-1119</orcidid><orcidid>https://orcid.org/0000-0002-2143-7063</orcidid><orcidid>https://orcid.org/0000-0002-3193-4020</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1520-9210
ispartof IEEE transactions on multimedia, 2021, Vol.23, p.3817-3827
issn 1520-9210
1941-0077
language eng
recordid cdi_hal_primary_oai_HAL_hal_03205745v1
source IEEE Xplore (Online service)
subjects Color
color gamut mapping
Computer Science
content characterization
content selection
Criteria
Image color analysis
Image Processing
Image quality
Measurement
Multimedia
Quality of experience
Reliability analysis
Toy manufacturing industry
Visualization
Wide color gamut
title Wide Color Gamut Image Content Characterization: Method, Evaluation, and Applications
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T10%3A01%3A25IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Wide%20Color%20Gamut%20Image%20Content%20Characterization:%20Method,%20Evaluation,%20and%20Applications&rft.jtitle=IEEE%20transactions%20on%20multimedia&rft.au=Lee,%20Junghyuk&rft.date=2021&rft.volume=23&rft.spage=3817&rft.epage=3827&rft.pages=3817-3827&rft.issn=1520-9210&rft.eissn=1941-0077&rft.coden=ITMUF8&rft_id=info:doi/10.1109/TMM.2020.3032026&rft_dat=%3Cproquest_hal_p%3E2583636674%3C/proquest_hal_p%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c367t-b62a6e8ab7736c13ff54d6882f550354c28ed18ea6274a26e00a2e8aa1bbc2b73%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2583636674&rft_id=info:pmid/&rft_ieee_id=9234679&rfr_iscdi=true