Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/140387
Title: | Objective quality assessment and perceptual compression of screen content images | Authors: | Wang, Shiqi Gu, Ke Zeng, Kai Wang, Zhou Lin, Weisi |
Keywords: | Engineering::Computer science and engineering | Issue Date: | 2016 | Source: | Wang, S., Gu, K., Zeng, K., Wang, Z., & Lin, W. (2018). Objective quality assessment and perceptual compression of screen content images. IEEE Computer Graphics and Applications, 38(1), 47-58. doi:10.1109/MCG.2016.46 | Journal: | IEEE Computer Graphics and Applications | Abstract: | Screen content image (SCI) has recently emerged as an active topic due to the rapidly increasing demand in many graphically rich services such as wireless displays and virtual desktops. SCIs are often composed of pictorial regions and computer generated textual/graphical content, which exhibit different statistical properties that often lead to different viewer behaviors. Inspired by this, we propose an objective quality assessment approach for SCIs that incorporates both visual field adaptation and information content weighting into structural similarity based local quality assessment. Furthermore, we develop a perceptual screen content coding scheme based on the newly proposed quality assessment measure, targeting at further improving the SCI compression performance. Experimental results show that the proposed quality assessment method not only better predicts the perceptual quality of SCIs, but also demonstrates great potentials in the design of perceptually optimal SCI compression schemes. | URI: | https://hdl.handle.net/10356/140387 | ISSN: | 0272-1716 | DOI: | 10.1109/MCG.2016.46 | Rights: | © 2018 IEEE. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | SCSE Journal Articles |
SCOPUSTM
Citations
33
Updated on Mar 2, 2021
PublonsTM
Citations
27
Updated on Mar 7, 2021
Page view(s)
20
Updated on Mar 8, 2021
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.