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Video quality assessment using content-weighted spatial and temporal pooling method

[+] Author Affiliations
Chaofeng Li

University of Chinese Academy of Sciences, Laboratory of Computational Geodynamics, No.19 Yuquan Road, Beijing 100049, China

Jiangnan University, School of Internet of Things Engineering, No. 1800 Lihu Road, Wuxi 214122, China

Feng Pan, Xiaojun Wu, Yun-Hao Yuan, Wei Fang

Jiangnan University, School of Internet of Things Engineering, No. 1800 Lihu Road, Wuxi 214122, China

Yiwen Ju

University of Chinese Academy of Sciences, Laboratory of Computational Geodynamics, No.19 Yuquan Road, Beijing 100049, China

J. Electron. Imaging. 24(5), 053001 (Sep 01, 2015). doi:10.1117/1.JEI.24.5.053001
History: Received February 9, 2015; Accepted July 2, 2015
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Abstract.  Video quality assessment plays an important role in video processing and communication applications. We propose a full reference video quality metric by combining a content-weighted spatial pooling strategy with a temporal pooling strategy. All pixels in a frame are classified into edge, texture, and smooth regions, and their structural similarity image index (SSIM) maps are divided into increasing and saturated regions by the curve of their SSIM values, then a content weight method is applied to increasing regions to get the score of an image frame. Finally, a temporal pooling method is used to get the overall video quality. Experimental results on the LIVE and IVP video quality databases show our proposed method works well in matching subjective scores.

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Citation

Chaofeng Li ; Feng Pan ; Xiaojun Wu ; Yiwen Ju ; Yun-Hao Yuan, et al.
"Video quality assessment using content-weighted spatial and temporal pooling method", J. Electron. Imaging. 24(5), 053001 (Sep 01, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.5.053001


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