16 March 2015 Content-aware video quality assessment: predicting human perception of quality using peak signal to noise ratio and spatial/temporal activity
Author Affiliations +
Abstract
Since the end-user of video-based systems is often a human observer, prediction of human perception of quality (HPoQ) is an important task for increasing the user satisfaction. Despite the large variety of objective video quality measures, one problem is the lack of generalizability. This is mainly due to the strong dependency between HPoQ and video content. Although this problem is well-known, few existing methods directly account for the influence of video content on HPoQ.

This paper propose a new method to predict HPoQ by using simple distortion measures and introducing video content features in their computation. Our methodology is based on analyzing the level of spatio-temporal activity and combining HPoQ content related parameters with simple distortion measures. Our results show that even very simple distortion measures such as PSNR and simple spatio-temporal activity measures lead to good results. Results over four different public video quality databases show that the proposed methodology, while faster and simpler, is competitive with current state-of-the-art methods, i.e., correlations between objective and subjective assessment higher than 80% and it is only two times slower than PSNR.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
B. Ortiz-Jaramillo, J. Niño-Castañeda, Ljiljana Platiša, W. Philips, "Content-aware video quality assessment: predicting human perception of quality using peak signal to noise ratio and spatial/temporal activity", Proc. SPIE 9399, Image Processing: Algorithms and Systems XIII, 939917 (16 March 2015); doi: 10.1117/12.2083026; https://doi.org/10.1117/12.2083026
PROCEEDINGS
12 PAGES


SHARE
Back to Top