Improved Sensitivity of No-Reference Image Visual Quality Metrics to the Presence of Noise

Sheyda Ghanbaralizadeh Bahnemiri; Mykola Ponomarenko; Karen Egiazarian

doi:10.1007/978-3-031-31435-3_14

Improved Sensitivity of No-Reference Image Visual Quality Metrics to the Presence of Noise

Sheyda Ghanbaralizadeh Bahnemiri, Mykola Ponomarenko, Karen Egiazarian

Tietotekniikka

Tutkimustuotos: Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

Abstrakti

A problem of no-reference image visual quality assessment when images are corrupted by noise is considered in this paper. A specialized image set is proposed for the following two tasks: automatic verification of sensitivity of no-reference image visual quality metrics to noise, and analysis of blind noise level estimation methods. As a result, a method to improve the sensitivity of a given no reference quality metric to the presence of noise is proposed by combining this metric with a noise level estimator. The proposed method allows to significantly decrease a probability of wrong quality predictions for noisy images. Efficiency of usage of different noise level estimators in the proposed combined metrics is analyzed.

Alkuperäiskieli	Englanti
Otsikko	Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings
Toimittajat	Rikke Gade, Michael Felsberg, Joni-Kristian Kämäräinen
Kustantaja	Springer
Sivut	201-214
Sivumäärä	14
ISBN (painettu)	978-3-031-31434-6
DOI - pysyväislinkit	https://doi.org/10.1007/978-3-031-31435-3_14
Tila	Julkaistu - 2023
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisussa
Tapahtuma	Scandinavian Conference on Image Analysis - Lapland, Suomi Kesto: 18 huhtik. 2023 → 21 huhtik. 2023

Julkaisusarja

Nimi	Lecture Notes in Computer Science
Vuosikerta	13885 LNCS
ISSN (painettu)	0302-9743
ISSN (elektroninen)	1611-3349

Conference

Conference	Scandinavian Conference on Image Analysis
Maa/Alue	Suomi
Kaupunki	Lapland
Ajanjakso	18/04/23 → 21/04/23

Julkaisufoorumi-taso

Jufo-taso 1

!!ASJC Scopus subject areas

Theoretical Computer Science
Yleinen tietojenkäsittelytiede

Pääsy asiakirjaan

10.1007/978-3-031-31435-3_14

Siteeraa tätä

Bahnemiri, S. G., Ponomarenko, M., & Egiazarian, K. (2023). Improved Sensitivity of No-Reference Image Visual Quality Metrics to the Presence of Noise. teoksessa R. Gade, M. Felsberg, & J.-K. Kämäräinen (Toimittajat), Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings (Sivut 201-214). (Lecture Notes in Computer Science; Vuosikerta 13885 LNCS). Springer. https://doi.org/10.1007/978-3-031-31435-3_14

Bahnemiri, Sheyda Ghanbaralizadeh ; Ponomarenko, Mykola ; Egiazarian, Karen. / Improved Sensitivity of No-Reference Image Visual Quality Metrics to the Presence of Noise. Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings. Toimittaja / Rikke Gade ; Michael Felsberg ; Joni-Kristian Kämäräinen. Springer, 2023. Sivut 201-214 (Lecture Notes in Computer Science).

@inproceedings{1568eecea91f49d981a26fc0b268dcbf,

title = "Improved Sensitivity of No-Reference Image Visual Quality Metrics to the Presence of Noise",

abstract = "A problem of no-reference image visual quality assessment when images are corrupted by noise is considered in this paper. A specialized image set is proposed for the following two tasks: automatic verification of sensitivity of no-reference image visual quality metrics to noise, and analysis of blind noise level estimation methods. As a result, a method to improve the sensitivity of a given no reference quality metric to the presence of noise is proposed by combining this metric with a noise level estimator. The proposed method allows to significantly decrease a probability of wrong quality predictions for noisy images. Efficiency of usage of different noise level estimators in the proposed combined metrics is analyzed.",

keywords = "Blind noise level estimation, Deep neural networks, Image visual quality assessment, No-reference image quality metrics",

author = "Bahnemiri, \{Sheyda Ghanbaralizadeh\} and Mykola Ponomarenko and Karen Egiazarian",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; Scandinavian Conference on Image Analysis ; Conference date: 18-04-2023 Through 21-04-2023",

year = "2023",

doi = "10.1007/978-3-031-31435-3\_14",

language = "English",

isbn = "978-3-031-31434-6",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "201--214",

editor = "Rikke Gade and Michael Felsberg and Joni-Kristian K{\"a}m{\"a}r{\"a}inen",

booktitle = "Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings",

}

Bahnemiri, SG, Ponomarenko, M & Egiazarian, K 2023, Improved Sensitivity of No-Reference Image Visual Quality Metrics to the Presence of Noise. julkaisussa R Gade, M Felsberg & J-K Kämäräinen (toim), Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings. Lecture Notes in Computer Science, Vuosikerta 13885 LNCS, Springer, Sivut 201-214, Scandinavian Conference on Image Analysis, Lapland, Suomi, 18/04/23. https://doi.org/10.1007/978-3-031-31435-3_14

Improved Sensitivity of No-Reference Image Visual Quality Metrics to the Presence of Noise. / Bahnemiri, Sheyda Ghanbaralizadeh; Ponomarenko, Mykola ; Egiazarian, Karen.
Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings. toim. / Rikke Gade; Michael Felsberg; Joni-Kristian Kämäräinen. Springer, 2023. s. 201-214 (Lecture Notes in Computer Science; Vuosikerta 13885 LNCS).

Tutkimustuotos: Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

TY - GEN

T1 - Improved Sensitivity of No-Reference Image Visual Quality Metrics to the Presence of Noise

AU - Bahnemiri, Sheyda Ghanbaralizadeh

AU - Ponomarenko, Mykola

AU - Egiazarian, Karen

PY - 2023

Y1 - 2023

N2 - A problem of no-reference image visual quality assessment when images are corrupted by noise is considered in this paper. A specialized image set is proposed for the following two tasks: automatic verification of sensitivity of no-reference image visual quality metrics to noise, and analysis of blind noise level estimation methods. As a result, a method to improve the sensitivity of a given no reference quality metric to the presence of noise is proposed by combining this metric with a noise level estimator. The proposed method allows to significantly decrease a probability of wrong quality predictions for noisy images. Efficiency of usage of different noise level estimators in the proposed combined metrics is analyzed.

AB - A problem of no-reference image visual quality assessment when images are corrupted by noise is considered in this paper. A specialized image set is proposed for the following two tasks: automatic verification of sensitivity of no-reference image visual quality metrics to noise, and analysis of blind noise level estimation methods. As a result, a method to improve the sensitivity of a given no reference quality metric to the presence of noise is proposed by combining this metric with a noise level estimator. The proposed method allows to significantly decrease a probability of wrong quality predictions for noisy images. Efficiency of usage of different noise level estimators in the proposed combined metrics is analyzed.

KW - Blind noise level estimation

KW - Deep neural networks

KW - Image visual quality assessment

KW - No-reference image quality metrics

U2 - 10.1007/978-3-031-31435-3_14

DO - 10.1007/978-3-031-31435-3_14

M3 - Conference contribution

AN - SCOPUS:85161375798

SN - 978-3-031-31434-6

T3 - Lecture Notes in Computer Science

SP - 201

EP - 214

BT - Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings

A2 - Gade, Rikke

A2 - Felsberg, Michael

A2 - Kämäräinen, Joni-Kristian

PB - Springer

T2 - Scandinavian Conference on Image Analysis

Y2 - 18 April 2023 through 21 April 2023

ER -

Improved Sensitivity of No-Reference Image Visual Quality Metrics to the Presence of Noise

Abstrakti

Julkaisusarja

Conference

Julkaisufoorumi-taso

!!ASJC Scopus subject areas

Pääsy asiakirjaan

Sormenjälki

Siteeraa tätä