Saliency and Texture Information Based Full-Reference Quality Metrics for Video QoE Assessment

被引:0
|
作者
Luo, Qian [1 ]
Geng, Yang [1 ]
Liu, Jichun [1 ]
Li, Wenjing [1 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China
关键词
PACKETS;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we discuss how to assess video Quality of Experience (QoE) with image saliency and texture information extracted from original and distorted video sequences. Based on this information, we proposed two categories of full-reference quality metrics. The first category of metrics considers spatial distortions measured by MSE and SSIM in terms of saliency weighted images, saliency maps and texture maps. The second category of metrics are constructed by considering temporal distortions, which also includes the above three aspects. Then the temporal MSE between original and distorted video sequences is computed frame-by-frame. Thus altogether 9 metrics are obtained. With these metrics and subjective MOS from both the LIVE dataset and our own dataset, we conduct Neural Net fitting to measure the performance. Finally the detailed comparisons with mainstream models verify the effectiveness of the proposed model.
引用
收藏
页数:6
相关论文
共 50 条
  • [31] Full-Reference Stability Assessment of Digital Video Stabilization Based on Riemannian Metric
    Zhang, Lei
    Zheng, Qing-Zhuo
    Liu, Hong-Kang
    Huang, Hua
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 27 (12) : 6051 - 6063
  • [32] FULL-REFERENCE IMAGE QUALITY ASSESSMENT BASED ON THE ANALYSIS OF DISTORTION PROCESS
    Ma, Xiaoyu
    Jiang, Xiuhua
    Guo, Xiaoqiang
    2017 4TH INTERNATIONAL CONFERENCE ON SYSTEMS AND INFORMATICS (ICSAI), 2017, : 1256 - 1260
  • [33] Neural Network-Based Full-Reference Image Quality Assessment
    Bosse, Sebastian
    Maniry, Dominique
    Mueller, Klaus-Robert
    Wiegand, Thomas
    Samek, Wojciech
    2016 PICTURE CODING SYMPOSIUM (PCS), 2016,
  • [34] Full-Reference Image Quality Assessment Approach Based on Image Separation
    Wang, Bin
    PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ADVANCED ENGINEERING MATERIALS AND TECHNOLOGY, 2015, 38 : 524 - 527
  • [35] Full-Reference Image Quality Assessment Measure Based on Color Distortion
    Seghir, Zianou Ahmed
    Hachouf, Fella
    COMPUTER SCIENCE AND ITS APPLICATIONS, CIIA 2015, 2015, 456 : 66 - 77
  • [36] Two-Dimensional Approach to Full-Reference Image Quality Assessment Based on Positional Structural Information
    Capodiferro, Licia
    Jacovitti, Giovanni
    Di Claudio, Elio D.
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2012, 21 (02) : 505 - 516
  • [37] Full-Reference Stereoscopic Video Quality Assessment Using a Motion Sensitive HVS Model
    Galkandage, Chathura
    Calic, Janko
    Dogan, Safak
    Guillemaut, Jean-Yves
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2021, 31 (02) : 452 - 466
  • [38] Applicability limitations of differentiable full-reference image-quality metrics
    Siniukov, Maksim
    Kulikov, Dmitriy
    Vatolin, Dmitriy
    2023 DATA COMPRESSION CONFERENCE, DCC, 2023, : 363 - 363
  • [39] A Full-Reference Quality Assessment Metric for Cartoon Images
    Li, Chunyi
    Zhang, Zicheng
    Sun, Wei
    Min, Xiongkuo
    Zhai, Guangtao
    2022 IEEE 24TH INTERNATIONAL WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING (MMSP), 2022,
  • [40] No Reference Quality Assessment of Stereo Video Based on Saliency and Sparsity
    Yang, Jiachen
    Ji, Chunqi
    Jiang, Bin
    Lu, Wen
    Meng, Qinggang
    IEEE TRANSACTIONS ON BROADCASTING, 2018, 64 (02) : 341 - 353