DocumentCode
1400912
Title
Study of Subjective and Objective Quality Assessment of Video
Author
Seshadrinathan, Kalpana ; Soundararajan, Rajiv ; Bovik, Alan Conrad ; Cormack, Lawrence K.
Author_Institution
Intel Corp., Chandler, AZ, USA
Volume
19
Issue
6
fYear
2010
fDate
6/1/2010 12:00:00 AM
Firstpage
1427
Lastpage
1441
Abstract
We present the results of a recent large-scale subjective study of video quality on a collection of videos distorted by a variety of application-relevant processes. Methods to assess the visual quality of digital videos as perceived by human observers are becoming increasingly important, due to the large number of applications that target humans as the end users of video. Owing to the many approaches to video quality assessment (VQA) that are being developed, there is a need for a diverse independent public database of distorted videos and subjective scores that is freely available. The resulting Laboratory for Image and Video Engineering (LIVE) Video Quality Database contains 150 distorted videos (obtained from ten uncompressed reference videos of natural scenes) that were created using four different commonly encountered distortion types. Each video was assessed by 38 human subjects, and the difference mean opinion scores (DMOS) were recorded. We also evaluated the performance of several state-of-the-art, publicly available full-reference VQA algorithms on the new database. A statistical evaluation of the relative performance of these algorithms is also presented. The database has a dedicated web presence that will be maintained as long as it remains relevant and the data is available online.
Keywords
distortion; natural scenes; statistical analysis; video signal processing; visual perception; LIVE; application-relevant processes; digital videos; distorted videos; laboratory for image and video engineering; natural scenes; statistical evaluation; video distortion; video quality assessment; video quality database; Full reference; LIVE video quality database; human visual system; perceptual quality assessment; video quality; visual perception; Algorithms; Humans; Image Interpretation, Computer-Assisted; Observer Variation; Reproducibility of Results; Sensitivity and Specificity; Video Recording; Visual Perception;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2010.2042111
Filename
5404314
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