Human-Visual-System-Inspired Underwater Image Quality Measures
Тип публикации: Journal Article
Дата публикации: 2016-07-01
scimago Q1
wos Q1
БС1
SJR: 1.003
CiteScore: 9.3
Impact factor: 5.3
ISSN: 03649059, 15581691, 23737786
Electrical and Electronic Engineering
Mechanical Engineering
Ocean Engineering
Краткое описание
Underwater images suffer from blurring effects, low contrast, and grayed out colors due to the absorption and scattering effects under the water. Many image enhancement algorithms for improving the visual quality of underwater images have been developed. Unfortunately, no well-accepted objective measure exists that can evaluate the quality of underwater images similar to human perception. Predominant underwater image processing algorithms use either a subjective evaluation, which is time consuming and biased, or a generic image quality measure, which fails to consider the properties of underwater images. To address this problem, a new nonreference underwater image quality measure (UIQM) is presented in this paper. The UIQM comprises three underwater image attribute measures: the underwater image colorfulness measure (UICM), the underwater image sharpness measure (UISM), and the underwater image contrast measure (UIConM). Each attribute is selected for evaluating one aspect of the underwater image degradation, and each presented attribute measure is inspired by the properties of human visual systems (HVSs). The experimental results demonstrate that the measures effectively evaluate the underwater image quality in accordance with the human perceptions. These measures are also used on the AirAsia 8501 wreckage images to show their importance in practical applications.
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Panetta K., Gao C., Agaian S. Human-Visual-System-Inspired Underwater Image Quality Measures // IEEE Journal of Oceanic Engineering. 2016. Vol. 41. No. 3. pp. 541-551.
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Panetta K., Gao C., Agaian S. Human-Visual-System-Inspired Underwater Image Quality Measures // IEEE Journal of Oceanic Engineering. 2016. Vol. 41. No. 3. pp. 541-551.
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TY - JOUR
DO - 10.1109/joe.2015.2469915
UR - https://doi.org/10.1109/joe.2015.2469915
TI - Human-Visual-System-Inspired Underwater Image Quality Measures
T2 - IEEE Journal of Oceanic Engineering
AU - Panetta, Karen
AU - Gao, Chen
AU - Agaian, Sos
PY - 2016
DA - 2016/07/01
PB - Institute of Electrical and Electronics Engineers (IEEE)
SP - 541-551
IS - 3
VL - 41
SN - 0364-9059
SN - 1558-1691
SN - 2373-7786
ER -
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@article{2016_Panetta,
author = {Karen Panetta and Chen Gao and Sos Agaian},
title = {Human-Visual-System-Inspired Underwater Image Quality Measures},
journal = {IEEE Journal of Oceanic Engineering},
year = {2016},
volume = {41},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
month = {jul},
url = {https://doi.org/10.1109/joe.2015.2469915},
number = {3},
pages = {541--551},
doi = {10.1109/joe.2015.2469915}
}
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Panetta, Karen, et al. “Human-Visual-System-Inspired Underwater Image Quality Measures.” IEEE Journal of Oceanic Engineering, vol. 41, no. 3, Jul. 2016, pp. 541-551. https://doi.org/10.1109/joe.2015.2469915.