Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/597666
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dc.contributor.authorKe Guen_US
dc.contributor.authorShiqi Wangen_US
dc.contributor.authorGuangtao Zhaien_US
dc.contributor.authorSiwei Maen_US
dc.contributor.authorXiaokang Yangen_US
dc.contributor.authorWeisi Linen_US
dc.contributor.authorWenjun Zhangen_US
dc.contributor.authorWen Gaoen_US
dc.date.accessioned2020-05-20T08:51:40Z-
dc.date.available2020-05-20T08:51:40Z-
dc.date.issued2016en_US
dc.identifier.issn1520-9210en_US
dc.identifier.issn1941-0077en_US
dc.identifier.other10.1109/TMM.2016.2518868en_US
dc.identifier.urihttp://localhost/handle/Hannan/177963en_US
dc.identifier.urihttp://localhost/handle/Hannan/597666-
dc.description.abstractHigh dynamic range (HDR) imaging techniques have been working constantly, actively, and validly in the fault detection and disease diagnosis in the astronomical and medical fields, and currently they have also gained much more attention from digital image processing and computer vision communities. While HDR imaging devices are starting to have friendly prices, HDR display devices are still out of reach of typical consumers. Due to the limited availability of HDR display devices, in most cases tone mapping operators (TMOs) are used to convert HDR images to standard low dynamic range (LDR) images for visualization. But existing TMOs cannot work effectively for all kinds of HDR images, with their performance largely depending on brightness, contrast, and structure properties of a scene. To accurately measure and compare the performance of distinct TMOs, in this paper develop an effective and efficient no-reference objective quality metric which can automatically assess LDR images created by different TMOs without access to the original HDR images. Our model is shown to be statistically superior to recent full- and no-reference quality measures on the existing tone-mapped image database and a new relevant database built in this work.en_US
dc.publisherIEEEen_US
dc.relation.haspart7384762.pdfen_US
dc.subjectno-reference (NR)|tone mapping|image quality assessment (IQA)|High dynamic range (HDR)|statistical naturalness|information entropy|structural preservationen_US
dc.titleBlind Quality Assessment of Tone-Mapped Images Via Analysis of Information, Naturalness, and Structureen_US
dc.typeArticleen_US
dc.journal.volume18en_US
dc.journal.issue3en_US
dc.journal.titleIEEE Transactions on Multimediaen_US
Appears in Collections:2016

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Full metadata record
DC FieldValueLanguage
dc.contributor.authorKe Guen_US
dc.contributor.authorShiqi Wangen_US
dc.contributor.authorGuangtao Zhaien_US
dc.contributor.authorSiwei Maen_US
dc.contributor.authorXiaokang Yangen_US
dc.contributor.authorWeisi Linen_US
dc.contributor.authorWenjun Zhangen_US
dc.contributor.authorWen Gaoen_US
dc.date.accessioned2020-05-20T08:51:40Z-
dc.date.available2020-05-20T08:51:40Z-
dc.date.issued2016en_US
dc.identifier.issn1520-9210en_US
dc.identifier.issn1941-0077en_US
dc.identifier.other10.1109/TMM.2016.2518868en_US
dc.identifier.urihttp://localhost/handle/Hannan/177963en_US
dc.identifier.urihttp://localhost/handle/Hannan/597666-
dc.description.abstractHigh dynamic range (HDR) imaging techniques have been working constantly, actively, and validly in the fault detection and disease diagnosis in the astronomical and medical fields, and currently they have also gained much more attention from digital image processing and computer vision communities. While HDR imaging devices are starting to have friendly prices, HDR display devices are still out of reach of typical consumers. Due to the limited availability of HDR display devices, in most cases tone mapping operators (TMOs) are used to convert HDR images to standard low dynamic range (LDR) images for visualization. But existing TMOs cannot work effectively for all kinds of HDR images, with their performance largely depending on brightness, contrast, and structure properties of a scene. To accurately measure and compare the performance of distinct TMOs, in this paper develop an effective and efficient no-reference objective quality metric which can automatically assess LDR images created by different TMOs without access to the original HDR images. Our model is shown to be statistically superior to recent full- and no-reference quality measures on the existing tone-mapped image database and a new relevant database built in this work.en_US
dc.publisherIEEEen_US
dc.relation.haspart7384762.pdfen_US
dc.subjectno-reference (NR)|tone mapping|image quality assessment (IQA)|High dynamic range (HDR)|statistical naturalness|information entropy|structural preservationen_US
dc.titleBlind Quality Assessment of Tone-Mapped Images Via Analysis of Information, Naturalness, and Structureen_US
dc.typeArticleen_US
dc.journal.volume18en_US
dc.journal.issue3en_US
dc.journal.titleIEEE Transactions on Multimediaen_US
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7384762.pdf816.2 kBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorKe Guen_US
dc.contributor.authorShiqi Wangen_US
dc.contributor.authorGuangtao Zhaien_US
dc.contributor.authorSiwei Maen_US
dc.contributor.authorXiaokang Yangen_US
dc.contributor.authorWeisi Linen_US
dc.contributor.authorWenjun Zhangen_US
dc.contributor.authorWen Gaoen_US
dc.date.accessioned2020-05-20T08:51:40Z-
dc.date.available2020-05-20T08:51:40Z-
dc.date.issued2016en_US
dc.identifier.issn1520-9210en_US
dc.identifier.issn1941-0077en_US
dc.identifier.other10.1109/TMM.2016.2518868en_US
dc.identifier.urihttp://localhost/handle/Hannan/177963en_US
dc.identifier.urihttp://localhost/handle/Hannan/597666-
dc.description.abstractHigh dynamic range (HDR) imaging techniques have been working constantly, actively, and validly in the fault detection and disease diagnosis in the astronomical and medical fields, and currently they have also gained much more attention from digital image processing and computer vision communities. While HDR imaging devices are starting to have friendly prices, HDR display devices are still out of reach of typical consumers. Due to the limited availability of HDR display devices, in most cases tone mapping operators (TMOs) are used to convert HDR images to standard low dynamic range (LDR) images for visualization. But existing TMOs cannot work effectively for all kinds of HDR images, with their performance largely depending on brightness, contrast, and structure properties of a scene. To accurately measure and compare the performance of distinct TMOs, in this paper develop an effective and efficient no-reference objective quality metric which can automatically assess LDR images created by different TMOs without access to the original HDR images. Our model is shown to be statistically superior to recent full- and no-reference quality measures on the existing tone-mapped image database and a new relevant database built in this work.en_US
dc.publisherIEEEen_US
dc.relation.haspart7384762.pdfen_US
dc.subjectno-reference (NR)|tone mapping|image quality assessment (IQA)|High dynamic range (HDR)|statistical naturalness|information entropy|structural preservationen_US
dc.titleBlind Quality Assessment of Tone-Mapped Images Via Analysis of Information, Naturalness, and Structureen_US
dc.typeArticleen_US
dc.journal.volume18en_US
dc.journal.issue3en_US
dc.journal.titleIEEE Transactions on Multimediaen_US
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7384762.pdf816.2 kBAdobe PDFThumbnail
Preview File