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CLC number: TN919.8

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Received: 2009-01-14

Revision Accepted: 2009-04-23

Crosschecked: 2009-10-18

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Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.12 P.1696~1704

http://doi.org/10.1631/jzus.A0920035


A video structural similarity quality metric based on a joint spatial-temporal visual attention model


Author(s):  Hua ZHANG, Xiang TIAN, Yao-wu CHEN

Affiliation(s):  Institute of Advanced Digital Technology and Instrumentation, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   emma_zhanghua@zju.edu.cn, xiang.t@163.com, cyw@mail.bme.zju.edu.cn

Key Words:  Quality assessment, Structural similarity (SSIM) index, Attended region, Visual attention shift


Hua ZHANG, Xiang TIAN, Yao-wu CHEN. A video structural similarity quality metric based on a joint spatial-temporal visual attention model[J]. Journal of Zhejiang University Science A, 2009, 10(12): 1696~1704.

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Abstract: 
Objective video quality assessment plays a very important role in multimedia signal processing. Several extensions of the structural similarity (SSIM) index could not predict the quality of the video sequence effectively. In this paper we propose a structural similarity quality metric for videos based on a spatial-temporal visual attention model. This model acquires the motion attended region and the distortion attended region by computing the motion features and the distortion contrast. It mimics the visual attention shifting between the two attended regions and takes the burst of error into account by introducing the non-linear weighting functions to give a much higher weighting factor to the extremely damaged frames. The proposed metric based on the model renders the final object quality rating of the whole video sequence and is validated using the 50 Hz video sequences of Video Quality Experts Group Phase I test database.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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