Eugene H. Ratzlaff
ICDAR 2001
Objective image and video quality measures play important roles in a variety of image and video processing applications, such as compression, communication, printing, analysis, registration, restoration, enhancement and watermarking. Most proposed quality assessment approaches in the literature are error sensitivity-based methods. In this paper, we follow a new philosophy in designing image and video quality metrics, which uses structural distortion as an estimate of perceived visual distortion. A computationally efficient approach is developed for full-reference (FR) video quality assessment. The algorithm is tested on the video quality experts group Phase I FR-TV test data set. © 2003 Elsevier B.V. All rights reserved.
Eugene H. Ratzlaff
ICDAR 2001
Bowen Alpern, Larry Carter
VIS 1991
Orly Stettiner, Dan Chazan
ICPR 1994
Alex Cozzi, Florentin Wörgötter
IJCV