Preferred scene evaluation based on experimental approach for the optimum parameters
In order to measure the parameters of consumers' preferred image quality, this research suggests the following image quality assessment factors; dynamic range, color, and contrast. They have both physical image quality factors and psychological characteristics from the previous researches. For...
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creator | Hyung Ju Park Seungwon Lee Dong Hwan Har |
description | In order to measure the parameters of consumers' preferred image quality, this research suggests the following image quality assessment factors; dynamic range, color, and contrast. They have both physical image quality factors and psychological characteristics from the previous researches. For measuring the optimum parameter ranges of preferred images, we select 100 images from various websites by contents; portrait, landscape, and nightscape; therefore a total of 300 images are collected based on over 30 recommendations by appreciators. We try to expect the generality from user's recommendations and the diversity of contents from different scenes on the web. We discovered the specific ranges of preferred image quality metrics. Throughout this research, we are able to measure the preferred image quality metrics ranges. Also, we expect the practical and specific dynamic range, color, and contrast information of preferred image quality to positively influence product development. |
doi_str_mv | 10.1109/ISCE.2014.6884420 |
format | Conference Proceeding |
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They have both physical image quality factors and psychological characteristics from the previous researches. For measuring the optimum parameter ranges of preferred images, we select 100 images from various websites by contents; portrait, landscape, and nightscape; therefore a total of 300 images are collected based on over 30 recommendations by appreciators. We try to expect the generality from user's recommendations and the diversity of contents from different scenes on the web. We discovered the specific ranges of preferred image quality metrics. Throughout this research, we are able to measure the preferred image quality metrics ranges. 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Also, we expect the practical and specific dynamic range, color, and contrast information of preferred image quality to positively influence product development.</description><subject>color</subject><subject>contrast</subject><subject>dynamic range</subject><subject>Field-flow fractionation</subject><subject>image quality</subject><subject>parameter</subject><issn>0747-668X</issn><issn>2159-1423</issn><isbn>9781479945924</isbn><isbn>1479945927</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2014</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkM1KxEAQhEdRcF33AcTLvEBiz08y6aOEVRcWFMzB29LJdNhI_phkRd_egHuqog4fVSXEvYJYKcDH3Ue-jTUoG6dZZq2GC7FBlynrEG2C2l6KlVYJRspqcyVW4KyL0jT7vBG30_QFoB0aXIniPXDNIbCXU8U9S_6m9kRzM_SypGmJF8M_I4em436mVtI4hoGqo6yHIOcjy2Gcm-7UyZECdTxzmO7EdU3txJuzrkXxvC3y12j_9rLLn_ZRgzBHaeUMooeEPfq0gtrVJimJAEFrT5VJMki8QgKjyGoPjtJ6mYgKtbNUmrV4-Mc2zHwYl4YUfg_nP8wfhH1TJA</recordid><startdate>201406</startdate><enddate>201406</enddate><creator>Hyung Ju Park</creator><creator>Seungwon Lee</creator><creator>Dong Hwan Har</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201406</creationdate><title>Preferred scene evaluation based on experimental approach for the optimum parameters</title><author>Hyung Ju Park ; Seungwon Lee ; Dong Hwan Har</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-6c7399d05ed9d6c0f7f35baa09022dac35805d19a031a42d07a6f781919274ab3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2014</creationdate><topic>color</topic><topic>contrast</topic><topic>dynamic range</topic><topic>Field-flow fractionation</topic><topic>image quality</topic><topic>parameter</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hyung Ju Park</creatorcontrib><creatorcontrib>Seungwon Lee</creatorcontrib><creatorcontrib>Dong Hwan Har</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hyung Ju Park</au><au>Seungwon Lee</au><au>Dong Hwan Har</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Preferred scene evaluation based on experimental approach for the optimum parameters</atitle><btitle>The 18th IEEE International Symposium on Consumer Electronics (ISCE 2014)</btitle><stitle>ISCE</stitle><date>2014-06</date><risdate>2014</risdate><spage>1</spage><epage>2</epage><pages>1-2</pages><issn>0747-668X</issn><eissn>2159-1423</eissn><eisbn>9781479945924</eisbn><eisbn>1479945927</eisbn><abstract>In order to measure the parameters of consumers' preferred image quality, this research suggests the following image quality assessment factors; dynamic range, color, and contrast. They have both physical image quality factors and psychological characteristics from the previous researches. For measuring the optimum parameter ranges of preferred images, we select 100 images from various websites by contents; portrait, landscape, and nightscape; therefore a total of 300 images are collected based on over 30 recommendations by appreciators. We try to expect the generality from user's recommendations and the diversity of contents from different scenes on the web. We discovered the specific ranges of preferred image quality metrics. Throughout this research, we are able to measure the preferred image quality metrics ranges. Also, we expect the practical and specific dynamic range, color, and contrast information of preferred image quality to positively influence product development.</abstract><pub>IEEE</pub><doi>10.1109/ISCE.2014.6884420</doi><tpages>2</tpages></addata></record> |
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subjects | color contrast dynamic range Field-flow fractionation image quality parameter |
title | Preferred scene evaluation based on experimental approach for the optimum parameters |
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