SRQM: A Video Quality Metric for Spatial Resolution Adaptation

Alex Mackin; Mariana Afonso; Fan Zhang; David Bull

doi:10.1109/PCS.2018.8456246

SRQM: A Video Quality Metric for Spatial Resolution Adaptation

Alex Mackin
, Mariana Afonso
, Fan Zhang
, David Bull

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

6 Citations (Scopus)

520 Downloads (Pure)

Abstract

This paper presents a full reference objective video quality metric (SRQM), which characterises the relationship between variations in spatial resolution and visual quality in the context of adaptive video formats. SRQM uses wavelet decomposition, subband combination with perceptually inspired weights, and spatial pooling, to estimate the relative quality between the frames of a high resolution reference video, and one that has been spatially adapted through a combination of down and upsampling. The uVI-SR video database is used to benchmark SRQM against five commonly-used quality metrics. The database contains 24 diverse video sequences that span a range of spatial resolutions up to UHD-I (3840× 2160). An in- depth analysis demonstrates that SRQM is statistically superior to the other quality metrics for all tested adaptation filters, and all with relatively low computational complexity.

Original language	English
Title of host publication	2018 Picture Coding Symposium 2018 (PCS 2018)
Subtitle of host publication	Proceedings of a meeting held 24-27 June 2018, San Francisco, California, USA
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	283-287
Number of pages	5
ISBN (Electronic)	9781538641606
ISBN (Print)	9781538641613
DOIs	https://doi.org/10.1109/PCS.2018.8456246
Publication status	Published - 5 Sept 2018
Event	33rd Picture Coding Symposium, PCS 2018 - San Francisco, United States Duration: 24 Jun 2018 → 27 Jun 2018

Publication series

Name
ISSN (Print)	2472-7822

Conference

Conference	33rd Picture Coding Symposium, PCS 2018
Country/Territory	United States
City	San Francisco
Period	24/06/18 → 27/06/18

Access to Document

10.1109/PCS.2018.8456246

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Mackin, A., Afonso, M., Zhang, F., & Bull, D. (2018). SRQM: A Video Quality Metric for Spatial Resolution Adaptation. In 2018 Picture Coding Symposium 2018 (PCS 2018): Proceedings of a meeting held 24-27 June 2018, San Francisco, California, USA (pp. 283-287). Article 8456246 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/PCS.2018.8456246

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title = "SRQM: A Video Quality Metric for Spatial Resolution Adaptation",

abstract = "This paper presents a full reference objective video quality metric (SRQM), which characterises the relationship between variations in spatial resolution and visual quality in the context of adaptive video formats. SRQM uses wavelet decomposition, subband combination with perceptually inspired weights, and spatial pooling, to estimate the relative quality between the frames of a high resolution reference video, and one that has been spatially adapted through a combination of down and upsampling. The uVI-SR video database is used to benchmark SRQM against five commonly-used quality metrics. The database contains 24 diverse video sequences that span a range of spatial resolutions up to UHD-I (3840× 2160). An in- depth analysis demonstrates that SRQM is statistically superior to the other quality metrics for all tested adaptation filters, and all with relatively low computational complexity.",

author = "Alex Mackin and Mariana Afonso and Fan Zhang and David Bull",

year = "2018",

month = sep,

day = "5",

doi = "10.1109/PCS.2018.8456246",

language = "English",

isbn = "9781538641613",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

pages = "283--287",

booktitle = "2018 Picture Coding Symposium 2018 (PCS 2018)",

address = "United States",

note = "33rd Picture Coding Symposium, PCS 2018 ; Conference date: 24-06-2018 Through 27-06-2018",

}

Mackin, A, Afonso, M, Zhang, F & Bull, D 2018, SRQM: A Video Quality Metric for Spatial Resolution Adaptation. in 2018 Picture Coding Symposium 2018 (PCS 2018): Proceedings of a meeting held 24-27 June 2018, San Francisco, California, USA., 8456246, Institute of Electrical and Electronics Engineers (IEEE), pp. 283-287, 33rd Picture Coding Symposium, PCS 2018, San Francisco, United States, 24/06/18. https://doi.org/10.1109/PCS.2018.8456246

SRQM: A Video Quality Metric for Spatial Resolution Adaptation. / Mackin, Alex; Afonso, Mariana; Zhang, Fan et al.
2018 Picture Coding Symposium 2018 (PCS 2018): Proceedings of a meeting held 24-27 June 2018, San Francisco, California, USA. Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 283-287 8456246.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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AU - Mackin, Alex

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AU - Zhang, Fan

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AB - This paper presents a full reference objective video quality metric (SRQM), which characterises the relationship between variations in spatial resolution and visual quality in the context of adaptive video formats. SRQM uses wavelet decomposition, subband combination with perceptually inspired weights, and spatial pooling, to estimate the relative quality between the frames of a high resolution reference video, and one that has been spatially adapted through a combination of down and upsampling. The uVI-SR video database is used to benchmark SRQM against five commonly-used quality metrics. The database contains 24 diverse video sequences that span a range of spatial resolutions up to UHD-I (3840× 2160). An in- depth analysis demonstrates that SRQM is statistically superior to the other quality metrics for all tested adaptation filters, and all with relatively low computational complexity.

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PB - Institute of Electrical and Electronics Engineers (IEEE)

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SRQM: A Video Quality Metric for Spatial Resolution Adaptation

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Intelligent Resampling Methods for Video Compression

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SRQM: A Video Quality Metric for Spatial Resolution Adaptation

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Intelligent Resampling Methods for Video Compression

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