The RR-PEVQ algorithm research based on active area detection for big data applications

Wei Jian Xu, Cai Dan Zhao, Hua Pei Chiang, Lianfen Huang, Yueh-Min Huang

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The reduced-reference video quality evaluation method uses only partial reference video information to evaluate the quality of deteriorated videos. This method can evaluate the quality of a video in real-time because less transmission bandwidth is required. Because the video active area attracts significant human eye attention, any deterioration in the active area will directly affect video evaluation results. Given the advantage of reduced reference model in VQM (Video Qualify Metric), this paper proposes a reduced reference evaluation model named RR-PEVQ (Reduced Reference Perceptual Evaluation of Video Quality) for weighting the active video area. According to the experimental results, the RR-PEVQ evaluation score is similar to that of the full reference PEVQ and the proposed method’s practicability is greatly improved for big data purposes.

Original languageEnglish
Pages (from-to)3507-3520
Number of pages14
JournalMultimedia Tools and Applications
Volume74
Issue number10
DOIs
Publication statusPublished - 2015 May 16

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Deterioration
Bandwidth
Big data

All Science Journal Classification (ASJC) codes

  • Software
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications

Cite this

Xu, Wei Jian ; Zhao, Cai Dan ; Chiang, Hua Pei ; Huang, Lianfen ; Huang, Yueh-Min. / The RR-PEVQ algorithm research based on active area detection for big data applications. In: Multimedia Tools and Applications. 2015 ; Vol. 74, No. 10. pp. 3507-3520.
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The RR-PEVQ algorithm research based on active area detection for big data applications. / Xu, Wei Jian; Zhao, Cai Dan; Chiang, Hua Pei; Huang, Lianfen; Huang, Yueh-Min.

In: Multimedia Tools and Applications, Vol. 74, No. 10, 16.05.2015, p. 3507-3520.

Research output: Contribution to journalArticle

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