Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/208153
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dc.contributor.authorZhihua Chenen_US
dc.contributor.authorZhenzhu Wangen_US
dc.contributor.authorBin Shengen_US
dc.contributor.authorChao Lien_US
dc.contributor.authorRuimin Shenen_US
dc.contributor.authorPing Lien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:58:08Z-
dc.date.available2020-04-06T07:58:08Z-
dc.date.issued2017en_US
dc.identifier.other10.1049/iet-ipr.2016.0989en_US
dc.identifier.urihttp://localhost/handle/Hannan/208153-
dc.description.abstractAs the standard colour space used by printers, Cyan, Magenta, Yellow, Black (CMYK) colour model is a subtractive colour space used to describe the printing process. Existing CMYK conversion methods rely on static conversion table, which may not preserve the subtle visual structures of images, due to the local visual contrast loss caused by the static colour mapping. Therefore, the authors propose a novel dynamic Red, Green, Blue (RGB)-to-CMYK colour conversion, which utilises the weighted entropy to extract the pixels with filter response change dramatically. They obtain the image activity map by combining these pixels with high skin probability regions, and optimise the colour conversion of each pixel to ensure that the ink used for each pixel can be saved, while the visual contrast can be preserved with ink-saving. In this way, their proposed technique can achieve dynamic CMYK colour conversion, in which the consumption of ink can be reduced without the loss of visual contrast. The experimental results have shown that their dynamic CMYK colour conversion saved 10-25% ink consumption compared with the static conversion method, while with high visual quality for the converted images.en_US
dc.format.extent539,en_US
dc.format.extent549en_US
dc.publisherIETen_US
dc.relation.haspart7972771.pdfen_US
dc.titleDynamic RGB-to-CMYK conversion using visual contrast optimisationen_US
dc.typeArticleen_US
dc.journal.volume11en_US
dc.journal.issue7en_US
Appears in Collections:2017

Files in This Item:
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7972771.pdf9.91 MBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorZhihua Chenen_US
dc.contributor.authorZhenzhu Wangen_US
dc.contributor.authorBin Shengen_US
dc.contributor.authorChao Lien_US
dc.contributor.authorRuimin Shenen_US
dc.contributor.authorPing Lien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:58:08Z-
dc.date.available2020-04-06T07:58:08Z-
dc.date.issued2017en_US
dc.identifier.other10.1049/iet-ipr.2016.0989en_US
dc.identifier.urihttp://localhost/handle/Hannan/208153-
dc.description.abstractAs the standard colour space used by printers, Cyan, Magenta, Yellow, Black (CMYK) colour model is a subtractive colour space used to describe the printing process. Existing CMYK conversion methods rely on static conversion table, which may not preserve the subtle visual structures of images, due to the local visual contrast loss caused by the static colour mapping. Therefore, the authors propose a novel dynamic Red, Green, Blue (RGB)-to-CMYK colour conversion, which utilises the weighted entropy to extract the pixels with filter response change dramatically. They obtain the image activity map by combining these pixels with high skin probability regions, and optimise the colour conversion of each pixel to ensure that the ink used for each pixel can be saved, while the visual contrast can be preserved with ink-saving. In this way, their proposed technique can achieve dynamic CMYK colour conversion, in which the consumption of ink can be reduced without the loss of visual contrast. The experimental results have shown that their dynamic CMYK colour conversion saved 10-25% ink consumption compared with the static conversion method, while with high visual quality for the converted images.en_US
dc.format.extent539,en_US
dc.format.extent549en_US
dc.publisherIETen_US
dc.relation.haspart7972771.pdfen_US
dc.titleDynamic RGB-to-CMYK conversion using visual contrast optimisationen_US
dc.typeArticleen_US
dc.journal.volume11en_US
dc.journal.issue7en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7972771.pdf9.91 MBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorZhihua Chenen_US
dc.contributor.authorZhenzhu Wangen_US
dc.contributor.authorBin Shengen_US
dc.contributor.authorChao Lien_US
dc.contributor.authorRuimin Shenen_US
dc.contributor.authorPing Lien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:58:08Z-
dc.date.available2020-04-06T07:58:08Z-
dc.date.issued2017en_US
dc.identifier.other10.1049/iet-ipr.2016.0989en_US
dc.identifier.urihttp://localhost/handle/Hannan/208153-
dc.description.abstractAs the standard colour space used by printers, Cyan, Magenta, Yellow, Black (CMYK) colour model is a subtractive colour space used to describe the printing process. Existing CMYK conversion methods rely on static conversion table, which may not preserve the subtle visual structures of images, due to the local visual contrast loss caused by the static colour mapping. Therefore, the authors propose a novel dynamic Red, Green, Blue (RGB)-to-CMYK colour conversion, which utilises the weighted entropy to extract the pixels with filter response change dramatically. They obtain the image activity map by combining these pixels with high skin probability regions, and optimise the colour conversion of each pixel to ensure that the ink used for each pixel can be saved, while the visual contrast can be preserved with ink-saving. In this way, their proposed technique can achieve dynamic CMYK colour conversion, in which the consumption of ink can be reduced without the loss of visual contrast. The experimental results have shown that their dynamic CMYK colour conversion saved 10-25% ink consumption compared with the static conversion method, while with high visual quality for the converted images.en_US
dc.format.extent539,en_US
dc.format.extent549en_US
dc.publisherIETen_US
dc.relation.haspart7972771.pdfen_US
dc.titleDynamic RGB-to-CMYK conversion using visual contrast optimisationen_US
dc.typeArticleen_US
dc.journal.volume11en_US
dc.journal.issue7en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7972771.pdf9.91 MBAdobe PDF