Eli Schwartz, Leonid Karlinsky, et al.
NeurIPS 2018
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.
Eli Schwartz, Leonid Karlinsky, et al.
NeurIPS 2018
Zhixian Yan, Dipanjan Chakraborty, et al.
EDBT 2011
Ligang Lu, Jack L. Kouloheris
IS&T/SPIE Electronic Imaging 2002
Jessica He, David Piorkowski, et al.
CHIWORK 2023