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Volume: 27 | Article ID: art00045
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No-Reference Image Quality Metric for Tone-Mapped Images
Muhammad Usman Khan
Imran Mehmood
Ming Ronnier Luo
Muhammad Farhan Mughal
  DOI :  10.2352/issn.2169-2629.2019.27.45  Published Online :  October 2019
Abstract

Tone-mapping operators transform high dynamic range (HDR) images into displayable low dynamic range (LDR) images. Image quality evaluation of these LDR images is not possible by comparison with their corresponding high dynamic range images. Hence, a no-reference image quality metric for tone-mapped LDR images is proposed based on the fitting to the present psychophysical results including different visual image quality attributes. Ten images, including HDR natural scenes, were tonemapped using six TMOs. They were used in the assessment and visual attributes were determined to predict the quality of these images. The visual attributes (brightness and Naturalness) were modeled using parameters derived from CAM16-UCS. Results showed that the quality prediction of the model had a reasonable degree of accuracy.

Journal Title : Color and Imaging Conference
Publisher Name : Society for Imaging Science and Technology
Subject Areas :
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 DOI 10.2352/issn.2169-2629.2019.27.45
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  Cite this article 

Muhammad Usman Khan, Imran Mehmood, Ming Ronnier Luo, Muhammad Farhan Mughal, "No-Reference Image Quality Metric for Tone-Mapped Images"  in Proc. IS&T 27th Color and Imaging Conf.,  2019,  pp 252 - 255,  https://doi.org/10.2352/issn.2169-2629.2019.27.45

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Copyright © Society for Imaging Science and Technology 2019
72010350
Color and Imaging Conference
color imaging conf
2166-9635
Society for Imaging Science and Technology
10.2352/issn.2169-2629.2019.27.45
2166-9635(20191021)2019:1L.252;1-
s45.phd
/ist/cic/2019/00002019/00000001/art00045
Articles
No-Reference Image Quality Metric for Tone-Mapped Images
KhanMuhammad Usman
MehmoodImran
LuoMing Ronnier
MughalMuhammad Farhan
21102019
2019
1
252
255
2019
Tone-mapping operators transform high dynamic range (HDR) images into displayable low dynamic range (LDR) images. Image quality evaluation of these LDR images is not possible by comparison with their corresponding high dynamic range images. Hence, a no-reference image quality metric for tone-mapped LDR images is proposed based on the fitting to the present psychophysical results including different visual image quality attributes. Ten images, including HDR natural scenes, were tonemapped using six TMOs. They were used in the assessment and visual attributes were determined to predict the quality of these images. The visual attributes (brightness and Naturalness) were modeled using parameters derived from CAM16-UCS. Results showed that the quality prediction of the model had a reasonable degree of accuracy.