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Image database TID2013: Peculiarities, results and perspectives

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Image database TID2013 : Peculiarities, results and perspectives. / Ponomarenko, Nikolay; Jin, Lina; Ieremeiev, Oleg; Lukin, Vladimir; Egiazarian, Karen; Astola, Jaakko; Vozel, Benoit; Chehdi, Kacem; Carli, Marco; Battisti, Federica; Jay Kuo, C. C.

In: Signal Processing: Image Communication, Vol. 30, 01.01.2015, p. 57-77.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Ponomarenko, N, Jin, L, Ieremeiev, O, Lukin, V, Egiazarian, K, Astola, J, Vozel, B, Chehdi, K, Carli, M, Battisti, F & Jay Kuo, CC 2015, 'Image database TID2013: Peculiarities, results and perspectives', Signal Processing: Image Communication, vol. 30, pp. 57-77. https://doi.org/10.1016/j.image.2014.10.009

APA

Ponomarenko, N., Jin, L., Ieremeiev, O., Lukin, V., Egiazarian, K., Astola, J., ... Jay Kuo, C. C. (2015). Image database TID2013: Peculiarities, results and perspectives. Signal Processing: Image Communication, 30, 57-77. https://doi.org/10.1016/j.image.2014.10.009

Vancouver

Ponomarenko N, Jin L, Ieremeiev O, Lukin V, Egiazarian K, Astola J et al. Image database TID2013: Peculiarities, results and perspectives. Signal Processing: Image Communication. 2015 Jan 1;30:57-77. https://doi.org/10.1016/j.image.2014.10.009

Author

Ponomarenko, Nikolay ; Jin, Lina ; Ieremeiev, Oleg ; Lukin, Vladimir ; Egiazarian, Karen ; Astola, Jaakko ; Vozel, Benoit ; Chehdi, Kacem ; Carli, Marco ; Battisti, Federica ; Jay Kuo, C. C. / Image database TID2013 : Peculiarities, results and perspectives. In: Signal Processing: Image Communication. 2015 ; Vol. 30. pp. 57-77.

Bibtex - Download

@article{6fde3c0ad031480981eedd396ca933aa,
title = "Image database TID2013: Peculiarities, results and perspectives",
abstract = "This paper describes a recently created image database, TID2013, intended for evaluation of full-reference visual quality assessment metrics. With respect to TID2008, the new database contains a larger number (3000) of test images obtained from 25 reference images, 24 types of distortions for each reference image, and 5 levels for each type of distortion. Motivations for introducing 7 new types of distortions and one additional level of distortions are given; examples of distorted images are presented. Mean opinion scores (MOS) for the new database have been collected by performing 985 subjective experiments with volunteers (observers) from five countries (Finland, France, Italy, Ukraine, and USA). The availability of MOS allows the use of the designed database as a fundamental tool for assessing the effectiveness of visual quality. Furthermore, existing visual quality metrics have been tested with the proposed database and the collected results have been analyzed using rank order correlation coefficients between MOS and considered metrics. These correlation indices have been obtained both considering the full set of distorted images and specific image subsets, for highlighting advantages and drawbacks of existing, state of the art, quality metrics. Approaches to thorough performance analysis for a given metric are presented to detect practical situations or distortion types for which this metric is not adequate enough to human perception. The created image database and the collected MOS values are freely available for downloading and utilization for scientific purposes.",
keywords = "Image denoising, Image lossy compression, Image visual quality metrics",
author = "Nikolay Ponomarenko and Lina Jin and Oleg Ieremeiev and Vladimir Lukin and Karen Egiazarian and Jaakko Astola and Benoit Vozel and Kacem Chehdi and Marco Carli and Federica Battisti and {Jay Kuo}, {C. C.}",
year = "2015",
month = "1",
day = "1",
doi = "10.1016/j.image.2014.10.009",
language = "English",
volume = "30",
pages = "57--77",
journal = "Signal Processing: Image Communication",
issn = "0923-5965",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Image database TID2013

T2 - Peculiarities, results and perspectives

AU - Ponomarenko, Nikolay

AU - Jin, Lina

AU - Ieremeiev, Oleg

AU - Lukin, Vladimir

AU - Egiazarian, Karen

AU - Astola, Jaakko

AU - Vozel, Benoit

AU - Chehdi, Kacem

AU - Carli, Marco

AU - Battisti, Federica

AU - Jay Kuo, C. C.

PY - 2015/1/1

Y1 - 2015/1/1

N2 - This paper describes a recently created image database, TID2013, intended for evaluation of full-reference visual quality assessment metrics. With respect to TID2008, the new database contains a larger number (3000) of test images obtained from 25 reference images, 24 types of distortions for each reference image, and 5 levels for each type of distortion. Motivations for introducing 7 new types of distortions and one additional level of distortions are given; examples of distorted images are presented. Mean opinion scores (MOS) for the new database have been collected by performing 985 subjective experiments with volunteers (observers) from five countries (Finland, France, Italy, Ukraine, and USA). The availability of MOS allows the use of the designed database as a fundamental tool for assessing the effectiveness of visual quality. Furthermore, existing visual quality metrics have been tested with the proposed database and the collected results have been analyzed using rank order correlation coefficients between MOS and considered metrics. These correlation indices have been obtained both considering the full set of distorted images and specific image subsets, for highlighting advantages and drawbacks of existing, state of the art, quality metrics. Approaches to thorough performance analysis for a given metric are presented to detect practical situations or distortion types for which this metric is not adequate enough to human perception. The created image database and the collected MOS values are freely available for downloading and utilization for scientific purposes.

AB - This paper describes a recently created image database, TID2013, intended for evaluation of full-reference visual quality assessment metrics. With respect to TID2008, the new database contains a larger number (3000) of test images obtained from 25 reference images, 24 types of distortions for each reference image, and 5 levels for each type of distortion. Motivations for introducing 7 new types of distortions and one additional level of distortions are given; examples of distorted images are presented. Mean opinion scores (MOS) for the new database have been collected by performing 985 subjective experiments with volunteers (observers) from five countries (Finland, France, Italy, Ukraine, and USA). The availability of MOS allows the use of the designed database as a fundamental tool for assessing the effectiveness of visual quality. Furthermore, existing visual quality metrics have been tested with the proposed database and the collected results have been analyzed using rank order correlation coefficients between MOS and considered metrics. These correlation indices have been obtained both considering the full set of distorted images and specific image subsets, for highlighting advantages and drawbacks of existing, state of the art, quality metrics. Approaches to thorough performance analysis for a given metric are presented to detect practical situations or distortion types for which this metric is not adequate enough to human perception. The created image database and the collected MOS values are freely available for downloading and utilization for scientific purposes.

KW - Image denoising

KW - Image lossy compression

KW - Image visual quality metrics

UR - http://www.scopus.com/inward/record.url?scp=84919839405&partnerID=8YFLogxK

U2 - 10.1016/j.image.2014.10.009

DO - 10.1016/j.image.2014.10.009

M3 - Article

VL - 30

SP - 57

EP - 77

JO - Signal Processing: Image Communication

JF - Signal Processing: Image Communication

SN - 0923-5965

ER -