Jehanzeb Mirza, Leonid Karlinsky, et al.
NeurIPS 2023
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.
Jehanzeb Mirza, Leonid Karlinsky, et al.
NeurIPS 2023
Tetsuro Morimura, Sei Kato
ICPR 2012
Jia Cui, Yonggang Deng, et al.
ASRU 2009
C.H. Morimoto, D. Koons, et al.
Image and Vision Computing