Xiaodan Song, Ching-Yung Lin, et al.
CVPRW 2004
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.
Xiaodan Song, Ching-Yung Lin, et al.
CVPRW 2004
Aditya Malik, Nalini Ratha, et al.
CAI 2024
Daniel A. Vaquero, Rogerio S. Feris, et al.
WACV 2009
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ICCV 2013