Signal Processing: Image Communication, special issue on “Objective Video Quality Metrics”, vol. 19, no. 2, pp. 121-132, Feb. 2004
Video Quality Assessment Based on Structural Distortion Measurement
1Laboratory for Computational Vision (LCV), New York University, New York, NY 10003
2Multimedia Technologies, IBM T. J. Watson Research Center, Yorktown Heights, NY 10598
3Laboratory for Image and Video Engineering (LIVE), The University of Texas at Austin, Austin, TX 78712
Abstract: Objective image/video quality measures play important roles in various image/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/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 (VQEG) Phase I FR-TV test data set.
Index Terms – image quality assessment, video quality assessment, human visual system, error sensitivity, structural distortion, video quality experts group (VQEG)