Open AccessParametric estimation of structural similarity degradation for video transmission over error‐prone networks
Author(s) -
Kwon YoungJae,
Lee JongSeok
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2013.1951
Subject(s) - computer science , video quality , degradation (telecommunications) , parametric statistics , coding (social sciences) , packet loss , transmission (telecommunications) , real time computing , parametric model , network packet , artificial intelligence , algorithm , metric (unit) , statistics , mathematics , computer network , telecommunications , engineering , operations management
A parametric model to estimate the degradation of objective video quality over error‐prone networks is proposed. The model estimates an expected quality degradation in terms of one of the most reliable perceptual quality metrics, structural similarities (SSIMs), for a given encoded video and network condition described by a packet loss rate. The simulation results demonstrate that the proposed model can estimate the expected SSIM degradation of H.264/ advanced video coding encoded videos with high accuracy.