Blind image quality evaluator with scale robustness

Ci Wang; Mei Li

doi:10.1109/ICASSP39728.2021.9414441

Blind image quality evaluator with scale robustness

Ci Wang, Mei Li

School of Communication and Electronic Engineering

East China Normal University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Image quality assessment (IQA) algorithms usually need define some visual-related features and build their relationship with image visual quality. Regardless of whether the features are extracted in spatial or frequency domain, these features are often sensitive to image resolution, resulting in that existing no-reference (NR) IQA algorithms are only efficient for images with similar resolution. In this paper, we propose a more generalized blind image quality evaluator with scale robustness (BIQESR) to assess image quality by locating the robust feature points in a multi-scale space. Compared with the state-of-the-art NR IQA methods, BIQESR has higher performance and stability for images with significantly different resolutions.

Original language	English
Title of host publication	2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2090-2094
Number of pages	5
ISBN (Electronic)	9781728176055
DOIs	https://doi.org/10.1109/ICASSP39728.2021.9414441
State	Published - 2021
Event	2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Virtual, Toronto, Canada Duration: 6 Jun 2021 → 11 Jun 2021

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2021-June
ISSN (Print)	1520-6149

Conference

Conference	2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021
Country/Territory	Canada
City	Virtual, Toronto
Period	6/06/21 → 11/06/21

Keywords

Different resolutions
Image quality assessment
Multi-scale space
No-reference

Access to Document

10.1109/ICASSP39728.2021.9414441

Cite this

Wang, C., & Li, M. (2021). Blind image quality evaluator with scale robustness. In 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Proceedings (pp. 2090-2094). (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2021-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP39728.2021.9414441

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title = "Blind image quality evaluator with scale robustness",

abstract = "Image quality assessment (IQA) algorithms usually need define some visual-related features and build their relationship with image visual quality. Regardless of whether the features are extracted in spatial or frequency domain, these features are often sensitive to image resolution, resulting in that existing no-reference (NR) IQA algorithms are only efficient for images with similar resolution. In this paper, we propose a more generalized blind image quality evaluator with scale robustness (BIQESR) to assess image quality by locating the robust feature points in a multi-scale space. Compared with the state-of-the-art NR IQA methods, BIQESR has higher performance and stability for images with significantly different resolutions.",

keywords = "Different resolutions, Image quality assessment, Multi-scale space, No-reference",

author = "Ci Wang and Mei Li",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 ; Conference date: 06-06-2021 Through 11-06-2021",

year = "2021",

doi = "10.1109/ICASSP39728.2021.9414441",

language = "英语",

series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2090--2094",

booktitle = "2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Proceedings",

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Wang, C & Li, M 2021, Blind image quality evaluator with scale robustness. in 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Proceedings. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2021-June, Institute of Electrical and Electronics Engineers Inc., pp. 2090-2094, 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021, Virtual, Toronto, Canada, 6/06/21. https://doi.org/10.1109/ICASSP39728.2021.9414441

Blind image quality evaluator with scale robustness. / Wang, Ci; Li, Mei.
2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2021. p. 2090-2094 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2021-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Wang, Ci

AU - Li, Mei

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N2 - Image quality assessment (IQA) algorithms usually need define some visual-related features and build their relationship with image visual quality. Regardless of whether the features are extracted in spatial or frequency domain, these features are often sensitive to image resolution, resulting in that existing no-reference (NR) IQA algorithms are only efficient for images with similar resolution. In this paper, we propose a more generalized blind image quality evaluator with scale robustness (BIQESR) to assess image quality by locating the robust feature points in a multi-scale space. Compared with the state-of-the-art NR IQA methods, BIQESR has higher performance and stability for images with significantly different resolutions.

AB - Image quality assessment (IQA) algorithms usually need define some visual-related features and build their relationship with image visual quality. Regardless of whether the features are extracted in spatial or frequency domain, these features are often sensitive to image resolution, resulting in that existing no-reference (NR) IQA algorithms are only efficient for images with similar resolution. In this paper, we propose a more generalized blind image quality evaluator with scale robustness (BIQESR) to assess image quality by locating the robust feature points in a multi-scale space. Compared with the state-of-the-art NR IQA methods, BIQESR has higher performance and stability for images with significantly different resolutions.

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KW - Image quality assessment

KW - Multi-scale space

KW - No-reference

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BT - 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 6 June 2021 through 11 June 2021

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Wang C, Li M. Blind image quality evaluator with scale robustness. In 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2021. p. 2090-2094. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP39728.2021.9414441

Blind image quality evaluator with scale robustness

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Keywords

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