
Content‐based bitrate model for perceived compression distortion evaluation of mobile video services
Author(s) -
Honglei Su,
Qi Liu,
Hao Gong,
Xiaohui Wang,
Huan Yang,
Zhenkuan Pan
Publication year - 2017
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.0318
Subject(s) - computer science , distortion (music) , compression (physics) , data compression , multimedia , computer vision , computer graphics (images) , telecommunications , bandwidth (computing) , amplifier , materials science , composite material
A novel bitrate model with low complexity is proposed for perceived compression distortion assessment of mobile video with low resolution, which is extremely useful in intermediate network nodes for quality monitoring. Without fully decoding, parameters are extracted by bitstream analysing, such as bitrate, frame type, quantisation parameter, DCT coefficient, motion vector. Bitrate is regarded as an essential parameter meanwhile the bitrate–MOS curve is determined by video content. Respectively, spatial factor is estimated using quantisation parameter and DCT coefficient and temporal factor is estimated using motion vector. Apart from bitrate, the spatial and temporal factors, which reflect the characteristic of video content, are considered in the proposed model to obtain a more accurate evaluation. Experimental results show that the overall performance of proposed model significantly outperforms that of the other five bitrate models in terms of widely used performance criteria, including the Pearson correlation coefficient (PCC), the Spearman rank‐order correlation coefficient (SROCC), the root‐mean‐squared error (RMSE) and the outlier ratio (OR).