Paper Info
Title
Hierarchical content importance-based video quality assessment for HEVC encoded videos transmitted over LTE networks.
Abstract
Hierarchical content importance-based frame degradation rate is proposed.Not only content type but also importance of the degraded content is quantified.Intra random access point loss rate is proposed. To improve the accuracy of assessment, many previous works take into account the video content. However, these previous works just only consider the video content, but do not consider the location and importance of the degraded content. Thus, this paper takes into account not only the video content, but also the location and importance of the degraded content, and proposes a hierarchical content importance-based video quality assessment. Firstly, we propose to use the hierarchical content importance-based frame degradation rate (HFDR) metric to quantify the importance of degraded content hierarchically. Secondly, we propose to use the intra random access point (IRAP) loss rate (ILR) metric to quantify the impact of IRAP. Finally, the proposed HFDR metric and ILR metric are subsequently used to develop an objective video quality assessment model. The experimental results show that the predicted mean opinion score (MOS) of the proposed method highly correlates with the actual MOS.
Year
DOI
Venue
2017
10.1016/j.jvcir.2016.12.010
J. Visual Communication and Image Representation
Keywords
Field
DocType
Content type,High efficiency video coding (HEVC),Long term evolution (LTE) network,Mean opinion score (MOS),Neural network,Quality of experience (QoE),Video quality assessment (VQA)
Content type,Data mining,Pattern recognition,Computer science,Mean opinion score,Subjective video quality,PEVQ,Artificial intelligence,Artificial neural network,Multimedia,Video quality,Random access
Journal
Volume
Issue
ISSN
43
C
1047-3203
Citations 
PageRank 
References 
1
0.35
25
Authors
4
Name
Order
Citations
PageRank
Jiefeng Guo122.05
Gong Hu210.69
Weijian Xu351.67
Lianfen Huang413232.83