Blind Tone-Mapped Image Quality Assessment Based on Brightest/Darkest Regions, Naturalness and Aesthetics
A tone-mapped image (TMI) converted from its high-dynamic-range image (HDRI) tends to appear overexposed in its brightest regions or underexposed in its darkest regions, resulting in inevitable loss of details and impaired naturalness and aesthetics. To address this issue, this paper proposes a nove...
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doaj-412a5979df454870b8fd5be617cee50b2021-03-29T20:33:18ZengIEEEIEEE Access2169-35362018-01-0162231224010.1109/ACCESS.2017.27823208186147Blind Tone-Mapped Image Quality Assessment Based on Brightest/Darkest Regions, Naturalness and AestheticsGangyi Jiang0https://orcid.org/0000-0002-9830-7048Hao Song1Mei Yu2Yang Song3Zongju Peng4Faculty of Information Science and Engineering, Ningbo University, Ningbo, ChinaFaculty of Information Science and Engineering, Ningbo University, Ningbo, ChinaFaculty of Information Science and Engineering, Ningbo University, Ningbo, ChinaFaculty of Information Science and Engineering, Ningbo University, Ningbo, ChinaFaculty of Information Science and Engineering, Ningbo University, Ningbo, ChinaA tone-mapped image (TMI) converted from its high-dynamic-range image (HDRI) tends to appear overexposed in its brightest regions or underexposed in its darkest regions, resulting in inevitable loss of details and impaired naturalness and aesthetics. To address this issue, this paper proposes a novel blind TMI quality assessment (BTMIQA) method for HDRIs used in different dynamic range displays. The brightest and darkest regions of the TMI are first defined and segmented, and their local detail features are used in combination with the global detail feature of the TMI to evaluate the detail distortion. The natural scene statistics features of the luminance and yellow channels of the TMI are then used to evaluate the luminance naturalness and chrominance naturalness, respectively. Subsequently, to predict the aesthetics of the TMI, a series of colorfulness features are extracted and concatenated in a final feature vector, which is used to evaluate the TMI quality by random forest regression. Experiments are performed on the TMI database and ESPL-LIVE high-dynamic-range database, and the results show the effectiveness of the proposed method. Compared with the existing TMI quality assessment methods, the proposed BTMIQA method is more consistent with human visual perception.https://ieeexplore.ieee.org/document/8186147/High dynamic range imagetone-mapped imageblind quality assessmentbrightest and darkest regionsdetail distortionnaturalness |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gangyi Jiang Hao Song Mei Yu Yang Song Zongju Peng |
spellingShingle |
Gangyi Jiang Hao Song Mei Yu Yang Song Zongju Peng Blind Tone-Mapped Image Quality Assessment Based on Brightest/Darkest Regions, Naturalness and Aesthetics IEEE Access High dynamic range image tone-mapped image blind quality assessment brightest and darkest regions detail distortion naturalness |
author_facet |
Gangyi Jiang Hao Song Mei Yu Yang Song Zongju Peng |
author_sort |
Gangyi Jiang |
title |
Blind Tone-Mapped Image Quality Assessment Based on Brightest/Darkest Regions, Naturalness and Aesthetics |
title_short |
Blind Tone-Mapped Image Quality Assessment Based on Brightest/Darkest Regions, Naturalness and Aesthetics |
title_full |
Blind Tone-Mapped Image Quality Assessment Based on Brightest/Darkest Regions, Naturalness and Aesthetics |
title_fullStr |
Blind Tone-Mapped Image Quality Assessment Based on Brightest/Darkest Regions, Naturalness and Aesthetics |
title_full_unstemmed |
Blind Tone-Mapped Image Quality Assessment Based on Brightest/Darkest Regions, Naturalness and Aesthetics |
title_sort |
blind tone-mapped image quality assessment based on brightest/darkest regions, naturalness and aesthetics |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2018-01-01 |
description |
A tone-mapped image (TMI) converted from its high-dynamic-range image (HDRI) tends to appear overexposed in its brightest regions or underexposed in its darkest regions, resulting in inevitable loss of details and impaired naturalness and aesthetics. To address this issue, this paper proposes a novel blind TMI quality assessment (BTMIQA) method for HDRIs used in different dynamic range displays. The brightest and darkest regions of the TMI are first defined and segmented, and their local detail features are used in combination with the global detail feature of the TMI to evaluate the detail distortion. The natural scene statistics features of the luminance and yellow channels of the TMI are then used to evaluate the luminance naturalness and chrominance naturalness, respectively. Subsequently, to predict the aesthetics of the TMI, a series of colorfulness features are extracted and concatenated in a final feature vector, which is used to evaluate the TMI quality by random forest regression. Experiments are performed on the TMI database and ESPL-LIVE high-dynamic-range database, and the results show the effectiveness of the proposed method. Compared with the existing TMI quality assessment methods, the proposed BTMIQA method is more consistent with human visual perception. |
topic |
High dynamic range image tone-mapped image blind quality assessment brightest and darkest regions detail distortion naturalness |
url |
https://ieeexplore.ieee.org/document/8186147/ |
work_keys_str_mv |
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