Study of subjective and objective quality assessment for screen content images

Xu WANG; Lei CAO; Yingying ZHU; Yun ZHANG; Jianmin JIANG; Sam KWONG

doi:10.1109/ICIP.2017.8296381

Study of subjective and objective quality assessment for screen content images

Xu WANG, Lei CAO, Yingying ZHU, Yun ZHANG, Jianmin JIANG, Sam KWONG

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

3 Citations (Scopus)

Abstract

In this paper, we present the results of a recent large-scale subjective study of image quality on a collection of screen contents distorted by a variety of application-relevant processes. With the development of multi-device interactive multimedia applications, metrics to predict the visual quality of screen content images (SCIs) as perceived by subjects are becoming fundamentally important. For developing the objective image quality assessment (IQA) method, there is a need for large-scale public database with diversity of distorted types and scene contents, and available subjective scores of distorted SCIs. The resulting Immersive Media Laboratory screen content image quality database (IML-SCIQD) contains 1250 distorted SCIs from 25 reference SCIs with 10 distortion types. Each image was rated by 35 human observers, and the different mean opinion scores (DMOS) were obtained after data processing. The performance comparison of 17 state-of-the-arts, publicly available IQA algorithms are evaluated on the new database. The database will be available online in our project website.

Original language	English
Title of host publication	2017 IEEE International Conference on Image Processing: Proceedings
Publisher	IEEE
Pages	750-754
Number of pages	5
ISBN (Electronic)	9781509021758
ISBN (Print)	9781509021765
DOIs	https://doi.org/10.1109/ICIP.2017.8296381
Publication status	Published - Sept 2017
Externally published	Yes
Event	2017 IEEE International Conference on Image Processing (ICIP) - China National Convention Center, Beijing, China Duration: 17 Sept 2017 → 20 Sept 2017

Conference

Conference	2017 IEEE International Conference on Image Processing (ICIP)
Country/Territory	China
City	Beijing
Period	17/09/17 → 20/09/17

Bibliographical note

This work was supported in part by the National Natural Science Foundation of China under Grant 61501299, 61672443, 31670553, 61602314, 61620106008 and 61471348, in part by the Guangdong Nature Science Foundation under Grant 2016A030310058 and 2016A030313043, in part by the Shenzhen Emerging Industries of the Strategic Basic Research Project under Grants JCYJ20150525092941043, JCYJ20160226191842793, JCYJ20130326105637578 and in part by the Project 2016049 supported by SZU R/D Fund.

Keywords

Image Quality Assessment
Screen content image

Access to Document

10.1109/ICIP.2017.8296381

Cite this

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title = "Study of subjective and objective quality assessment for screen content images",

abstract = "In this paper, we present the results of a recent large-scale subjective study of image quality on a collection of screen contents distorted by a variety of application-relevant processes. With the development of multi-device interactive multimedia applications, metrics to predict the visual quality of screen content images (SCIs) as perceived by subjects are becoming fundamentally important. For developing the objective image quality assessment (IQA) method, there is a need for large-scale public database with diversity of distorted types and scene contents, and available subjective scores of distorted SCIs. The resulting Immersive Media Laboratory screen content image quality database (IML-SCIQD) contains 1250 distorted SCIs from 25 reference SCIs with 10 distortion types. Each image was rated by 35 human observers, and the different mean opinion scores (DMOS) were obtained after data processing. The performance comparison of 17 state-of-the-arts, publicly available IQA algorithms are evaluated on the new database. The database will be available online in our project website.",

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author = "Xu WANG and Lei CAO and Yingying ZHU and Yun ZHANG and Jianmin JIANG and Sam KWONG",

note = "This work was supported in part by the National Natural Science Foundation of China under Grant 61501299, 61672443, 31670553, 61602314, 61620106008 and 61471348, in part by the Guangdong Nature Science Foundation under Grant 2016A030310058 and 2016A030313043, in part by the Shenzhen Emerging Industries of the Strategic Basic Research Project under Grants JCYJ20150525092941043, JCYJ20160226191842793, JCYJ20130326105637578 and in part by the Project 2016049 supported by SZU R/D Fund.; 2017 IEEE International Conference on Image Processing (ICIP) ; Conference date: 17-09-2017 Through 20-09-2017",

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AU - KWONG, Sam

N1 - This work was supported in part by the National Natural Science Foundation of China under Grant 61501299, 61672443, 31670553, 61602314, 61620106008 and 61471348, in part by the Guangdong Nature Science Foundation under Grant 2016A030310058 and 2016A030313043, in part by the Shenzhen Emerging Industries of the Strategic Basic Research Project under Grants JCYJ20150525092941043, JCYJ20160226191842793, JCYJ20130326105637578 and in part by the Project 2016049 supported by SZU R/D Fund.

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N2 - In this paper, we present the results of a recent large-scale subjective study of image quality on a collection of screen contents distorted by a variety of application-relevant processes. With the development of multi-device interactive multimedia applications, metrics to predict the visual quality of screen content images (SCIs) as perceived by subjects are becoming fundamentally important. For developing the objective image quality assessment (IQA) method, there is a need for large-scale public database with diversity of distorted types and scene contents, and available subjective scores of distorted SCIs. The resulting Immersive Media Laboratory screen content image quality database (IML-SCIQD) contains 1250 distorted SCIs from 25 reference SCIs with 10 distortion types. Each image was rated by 35 human observers, and the different mean opinion scores (DMOS) were obtained after data processing. The performance comparison of 17 state-of-the-arts, publicly available IQA algorithms are evaluated on the new database. The database will be available online in our project website.

AB - In this paper, we present the results of a recent large-scale subjective study of image quality on a collection of screen contents distorted by a variety of application-relevant processes. With the development of multi-device interactive multimedia applications, metrics to predict the visual quality of screen content images (SCIs) as perceived by subjects are becoming fundamentally important. For developing the objective image quality assessment (IQA) method, there is a need for large-scale public database with diversity of distorted types and scene contents, and available subjective scores of distorted SCIs. The resulting Immersive Media Laboratory screen content image quality database (IML-SCIQD) contains 1250 distorted SCIs from 25 reference SCIs with 10 distortion types. Each image was rated by 35 human observers, and the different mean opinion scores (DMOS) were obtained after data processing. The performance comparison of 17 state-of-the-arts, publicly available IQA algorithms are evaluated on the new database. The database will be available online in our project website.

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M3 - Conference paper (refereed)

SN - 9781509021765

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BT - 2017 IEEE International Conference on Image Processing: Proceedings

PB - IEEE

T2 - 2017 IEEE International Conference on Image Processing (ICIP)

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ER -

Study of subjective and objective quality assessment for screen content images

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Keywords

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