By Topic

Full-Reference Video Quality Metric for Fully Scalable and Mobile SVC Content

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Hosik Sohn ; Image and Video Systems Laboratory, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea ; Hana Yoo ; Wesley De Neve ; Cheon Seog Kim
more authors

Universal Multimedia Access (UMA) aims at enabling a straightforward consumption of multimedia content in heterogeneous usage environments. These usage environments may range from mobile devices in a wireless network to high-end desktop computers with wired network connectivity. Scalable video content can be used to deal with the restrictions and capabilities of diverse usage environments. However, in order to optimally tailor scalable video content along the temporal, spatial, or perceptual quality axis, a metric is needed that reliably models subjective video quality. The major contribution of this paper is the development of a novel full-reference quality metric for scalable video bit streams that are compliant with the H.264/AVC Scalable Video Coding (SVC) standard. The scalable video bit streams are intended to be used in mobile usage environments (e.g., adaptive video streaming to mobile devices). The proposed quality metric allows modeling the temporal, spatial, and perceptual quality characteristics of SVC-compliant bit streams by taking into account several properties of the compressed bit streams. These properties include the temporal and spatial variance of the video content, the frame rate, the spatial resolution, and PSNR values. An extensive number of subjective experiments have been conducted to construct and validate our quality metric. Experimental results show that the average correlation coefficient for the video sequences tested is as high as 0.95 (compared to a value of 0.60 when only using the traditional PSNR quality metric). The proposed quality metric also shows a performance that is a uniformly high for video sequences with different temporal and spatial characteristics.

Published in:

IEEE Transactions on Broadcasting  (Volume:56 ,  Issue: 3 )