Evaluation of quality scalability techniques for video transmission

TL;DR

This paper evaluates three main scalability techniques for video transmission, analyzing their impact on video quality metrics like PSNR and frame rate to determine the most effective method for adaptive streaming.

Contribution

It provides a comparative performance analysis of CGS, FGS, and MGS scalability techniques for video transmission, highlighting the advantages of MGS and rate-adaptive strategies.

Findings

MGS and rate-adaptive strategies improve video quality.

MGS helps reduce network congestion.

Performance varies with video quality metrics.

Abstract

The significant increase of the transmission of multimedia content over Internet are demanded new delivery strategies to assure a good quality of experience of the users. Transmission of video over packet networks is not an easy task due to multiple fluctuations of the network conditions. One possibility to improve the quality of some video streaming services is the combinate use of the scalable video coding and cross layer mechanisms that allow applications to adapt its traffic stream to the resources network that are available. In this paper, it is presented a performance evaluation of the three main scalability techniques: CGS (Coarse-Grained Scalability), FGS (Fine Grain scalability) and MGS (Medium Grain Scalability). In particular, we focus on determining what method is more appropriated for video transmission taking into account some video quality metrics like PSNR (Peak Signal-to-Noise Ratio) and decoded frame rate. The results reveal that the rate-adaptive strategy and the MGS technique help avoid or reduce the congestion in networks obtaining a better quality in the received videos.