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Algorithms 2017, 10(3), 72; doi:10.3390/a10030072

Hierarchical Gradient Similarity Based Video Quality Assessment Metric

1
College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2
Nari Group Corporation (State Grid Electric Power Research Institute), Nanjing 210003, China
3
School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
*
Author to whom correspondence should be addressed.
Received: 18 April 2017 / Revised: 19 June 2017 / Accepted: 19 June 2017 / Published: 23 June 2017
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Abstract

Video quality assessment (VQA) plays an important role in video applications for quality evaluation and resource allocation. It aims to evaluate video quality in a way that is consistent with human perception. In this letter, a hierarchical gradient similarity based VQA metric is proposed inspired by the structure of the primate visual cortex, in which visual information is processed through sequential visual areas. These areas are modeled with the corresponding measures to evaluate the overall perceptual quality. Experimental results on the LIVE database show that the proposed VQA metric significantly outperforms most of the state-of-the-art VQA metrics. View Full-Text
Keywords: hierarchical video quality assessment; human visual systems; primate visual cortex; full reference hierarchical video quality assessment; human visual systems; primate visual cortex; full reference
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MDPI and ACS Style

Yang, J.; Xiong, J.; Gui, G.; Song, R.; Luo, W.; Long, X. Hierarchical Gradient Similarity Based Video Quality Assessment Metric. Algorithms 2017, 10, 72.

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