Preprint Article Version 1 This version is not peer-reviewed

Hierarchical Gradient Similarity Based Video Quality Assessment Metric

Version 1 : Received: 14 April 2017 / Approved: 14 April 2017 / Online: 14 April 2017 (11:52:44 CEST)

How to cite: Yang, J.; Xiong, J.; Gui, G.; Song, R.; Luo, W.; Long, X. Hierarchical Gradient Similarity Based Video Quality Assessment Metric. Preprints 2017, 2017040088 (doi: 10.20944/preprints201704.0088.v1). Yang, J.; Xiong, J.; Gui, G.; Song, R.; Luo, W.; Long, X. Hierarchical Gradient Similarity Based Video Quality Assessment Metric. Preprints 2017, 2017040088 (doi: 10.20944/preprints201704.0088.v1).

Abstract

Video quality assessment (VQA) plays an important role in video applications for quality evaluation and resource allocation. It aims to evaluate the video quality consistent with the 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 the state-of-the-art VQA metrics.

Subject Areas

hierarchical video quality assessment; human visual systems; primate visual cortex; full reference

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