Asset Modeling using Serverless Computing
Srideepika Jayaraman, Chandra Reddy, et al.
Big Data 2021
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.
Srideepika Jayaraman, Chandra Reddy, et al.
Big Data 2021
Kun Wang, Juwei Shi, et al.
PACT 2011
Ligang Lu, Jack L. Kouloheris
IS&T/SPIE Electronic Imaging 2002
R.A. Gopinath, Markus Lang, et al.
ICIP 1994