Conrad Albrecht, Jannik Schneider, et al.
CVPR 2025
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.
Conrad Albrecht, Jannik Schneider, et al.
CVPR 2025
John R. Kender, Rick Kjeldsen
IEEE Transactions on Pattern Analysis and Machine Intelligence
James E. Gentile, Nalini Ratha, et al.
BTAS 2009
Simona Rabinovici-Cohen, Naomi Fridman, et al.
Cancers