Q-STAR: A Perceptual Video Quality Model Considering Impact of Spatial, Temporal, and Amplitude Resolutions
In this paper, we investigate the impact of spatial, temporal, and amplitude resolution on the perceptual quality of a compressed video. Subjective quality tests were carried out on a mobile device and a total of 189 processed video sequences with 10 source sequences included in the test. Subjective...
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| Veröffentlicht in: | IEEE transactions on image processing 2014-06, Vol.23 (6), p.2473-2486 |
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| creator | OU, Yen-Fu YUANYI XUE YAO WANG |
| description | In this paper, we investigate the impact of spatial, temporal, and amplitude resolution on the perceptual quality of a compressed video. Subjective quality tests were carried out on a mobile device and a total of 189 processed video sequences with 10 source sequences included in the test. Subjective data reveal that the impact of spatial resolution (SR), temporal resolution (TR), and quantization stepsize (QS) can each be captured by a function with a single content-dependent parameter, which indicates the decay rate of the quality with each resolution factor. The joint impact of SR, TR, and QS can be accurately modeled by the product of these three functions with only three parameters. The impact of SR and QS on the quality are independent of that of TR, but there are significant interactions between SR and QS. Furthermore, the model parameters can be predicted accurately from a few content features derived from the original video. The proposed model correlates well with the subjective ratings with a Pearson correlation coefficient of 0.985 when the model parameters are predicted from content features. The quality model is further validated on six other subjective rating data sets with very high accuracy and outperforms several well-known quality models. |
| doi_str_mv | 10.1109/TIP.2014.2303636 |
| format | Article |
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Subjective quality tests were carried out on a mobile device and a total of 189 processed video sequences with 10 source sequences included in the test. Subjective data reveal that the impact of spatial resolution (SR), temporal resolution (TR), and quantization stepsize (QS) can each be captured by a function with a single content-dependent parameter, which indicates the decay rate of the quality with each resolution factor. The joint impact of SR, TR, and QS can be accurately modeled by the product of these three functions with only three parameters. The impact of SR and QS on the quality are independent of that of TR, but there are significant interactions between SR and QS. Furthermore, the model parameters can be predicted accurately from a few content features derived from the original video. The proposed model correlates well with the subjective ratings with a Pearson correlation coefficient of 0.985 when the model parameters are predicted from content features. The quality model is further validated on six other subjective rating data sets with very high accuracy and outperforms several well-known quality models.</description><identifier>ISSN: 1057-7149</identifier><identifier>EISSN: 1941-0042</identifier><identifier>DOI: 10.1109/TIP.2014.2303636</identifier><identifier>PMID: 24815618</identifier><identifier>CODEN: IIPRE4</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Amplitudes ; Analytical models ; Applied sciences ; Coding, codes ; Compressed ; Decay rate ; Detection, estimation, filtering, equalization, prediction ; Exact sciences and technology ; Image processing ; Information, signal and communications theory ; Mathematical models ; Mobile communication systems ; Quality assessment ; Quantization (signal) ; Ratings ; Sampling, quantization ; Signal and communications theory ; Signal processing ; Signal, noise ; Spatial resolution ; Streaming media ; Telecommunications and information theory ; Temporal logic ; Testing ; Transaction processing</subject><ispartof>IEEE transactions on image processing, 2014-06, Vol.23 (6), p.2473-2486</ispartof><rights>2015 INIST-CNRS</rights><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Jun 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c410t-24e18495fac8728fb3658fe7cb1dea79012901db8a2014e9eb6aca416cb5c1733</citedby><cites>FETCH-LOGICAL-c410t-24e18495fac8728fb3658fe7cb1dea79012901db8a2014e9eb6aca416cb5c1733</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6728690$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6728690$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28528600$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24815618$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>OU, Yen-Fu</creatorcontrib><creatorcontrib>YUANYI XUE</creatorcontrib><creatorcontrib>YAO WANG</creatorcontrib><title>Q-STAR: A Perceptual Video Quality Model Considering Impact of Spatial, Temporal, and Amplitude Resolutions</title><title>IEEE transactions on image processing</title><addtitle>TIP</addtitle><addtitle>IEEE Trans Image Process</addtitle><description>In this paper, we investigate the impact of spatial, temporal, and amplitude resolution on the perceptual quality of a compressed video. Subjective quality tests were carried out on a mobile device and a total of 189 processed video sequences with 10 source sequences included in the test. Subjective data reveal that the impact of spatial resolution (SR), temporal resolution (TR), and quantization stepsize (QS) can each be captured by a function with a single content-dependent parameter, which indicates the decay rate of the quality with each resolution factor. The joint impact of SR, TR, and QS can be accurately modeled by the product of these three functions with only three parameters. The impact of SR and QS on the quality are independent of that of TR, but there are significant interactions between SR and QS. Furthermore, the model parameters can be predicted accurately from a few content features derived from the original video. The proposed model correlates well with the subjective ratings with a Pearson correlation coefficient of 0.985 when the model parameters are predicted from content features. The quality model is further validated on six other subjective rating data sets with very high accuracy and outperforms several well-known quality models.</description><subject>Amplitudes</subject><subject>Analytical models</subject><subject>Applied sciences</subject><subject>Coding, codes</subject><subject>Compressed</subject><subject>Decay rate</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Exact sciences and technology</subject><subject>Image processing</subject><subject>Information, signal and communications theory</subject><subject>Mathematical models</subject><subject>Mobile communication systems</subject><subject>Quality assessment</subject><subject>Quantization (signal)</subject><subject>Ratings</subject><subject>Sampling, quantization</subject><subject>Signal and communications theory</subject><subject>Signal processing</subject><subject>Signal, noise</subject><subject>Spatial resolution</subject><subject>Streaming media</subject><subject>Telecommunications and information theory</subject><subject>Temporal logic</subject><subject>Testing</subject><subject>Transaction processing</subject><issn>1057-7149</issn><issn>1941-0042</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqFkc1v1DAQxS0EoqVwR0JClhBSD2TxOLbjcFutaFmpiH4sXCPHmSCXJA52cuh_j6PdFqmXHiyP7N979swj5C2wFQArP--2lyvOQKx4znKVq2fkGEoBGWOCP081k0VWgCiPyKsYb1kiJaiX5IgLDVKBPiZ_rrKb3fr6C13TSwwWx2k2Hf3lGvT0KpVuuqPffYMd3fghpuPght9024_GTtS39GY0kzPdJ7rDfvRhqczQ0HU_JuncIL3G6Lt5ckn9mrxoTRfxzWE_IT_Pvu4237KLH-fbzfoiswLYlHGBoEUpW2N1wXVb50rqFgtbQ4OmKBnwtJpam6V1LLFWxhoBytbSQpHnJ-R07zsG_3fGOFW9ixa7zgzo51iBKkDm5TKzJ1HJk3Gapkzoh0forZ_DkBpJlFKQAtCLIdtTNvgYA7bVGFxvwl0FrFoyq1Jm1fLx6pBZkrw_GM91j82D4D6kBHw8ACZa07XBDNbF_5yWXCu2vP1uzzlEfLhWaYaqZPk_ErOlFQ</recordid><startdate>20140601</startdate><enddate>20140601</enddate><creator>OU, Yen-Fu</creator><creator>YUANYI XUE</creator><creator>YAO WANG</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Subjective quality tests were carried out on a mobile device and a total of 189 processed video sequences with 10 source sequences included in the test. Subjective data reveal that the impact of spatial resolution (SR), temporal resolution (TR), and quantization stepsize (QS) can each be captured by a function with a single content-dependent parameter, which indicates the decay rate of the quality with each resolution factor. The joint impact of SR, TR, and QS can be accurately modeled by the product of these three functions with only three parameters. The impact of SR and QS on the quality are independent of that of TR, but there are significant interactions between SR and QS. Furthermore, the model parameters can be predicted accurately from a few content features derived from the original video. The proposed model correlates well with the subjective ratings with a Pearson correlation coefficient of 0.985 when the model parameters are predicted from content features. 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| subjects | Amplitudes Analytical models Applied sciences Coding, codes Compressed Decay rate Detection, estimation, filtering, equalization, prediction Exact sciences and technology Image processing Information, signal and communications theory Mathematical models Mobile communication systems Quality assessment Quantization (signal) Ratings Sampling, quantization Signal and communications theory Signal processing Signal, noise Spatial resolution Streaming media Telecommunications and information theory Temporal logic Testing Transaction processing |
| title | Q-STAR: A Perceptual Video Quality Model Considering Impact of Spatial, Temporal, and Amplitude Resolutions |
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