A spatiotemporal most-apparent-distortion model for video quality assessment

This paper presents an algorithm for video quality assessment, spatiotemporal MAD (ST-MAD), which extends our previous image-based algorithm (MAD [1]) to take into account visual perception of motion artifacts. ST-MAD employs spatiotemporal "images" (STS images [2]) created by taking time-...

Full description

Saved in:
Bibliographic Details
Main Authors: Vu, P. V., Vu, C. T., Chandler, D. M.
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
distortion
Image processing
image quality
Motion pictures
Optical distortion
Quality assessment
Spatiotemporal phenomena
video quality
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents an algorithm for video quality assessment, spatiotemporal MAD (ST-MAD), which extends our previous image-based algorithm (MAD [1]) to take into account visual perception of motion artifacts. ST-MAD employs spatiotemporal "images" (STS images [2]) created by taking time-based slices of the original and distorted videos. Motion artifacts manifest in the STS images as spatial artifacts, which allows one to quantify motion-based distortion by using classical image-quality assessment techniques. ST-MAD estimates motion-based distortion by applying MAD's appearance-based model to compare the distorted video's STS images to the original video's STS images. This comparison is further adjusted by using optical-flow-derived weights designed to give greater precedence to fast-moving regions located toward the center of the video. Testing on the LIVE video database demonstrates that ST-MAD performs well in predicting video quality.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2011.6116171