Streaming video over wireless channels: Exploiting reduced-reference quality estimation at the user-side

  • Authors:

  • Luigi Atzori;Alessandro Floris;Giaime Ginesu;Daniele Giusto

  • Affiliations:

  • Department of Electrical and Electronic Engineering, University of Cagliari, 09123 Cagliari, Italy;Multimedia Communications Laboratory, CNIT, 09010 Pula, Italy;Department of Electrical and Electronic Engineering, University of Cagliari, 09123 Cagliari, Italy;Department of Electrical and Electronic Engineering, University of Cagliari, 09123 Cagliari, Italy

  • Venue:
  • Image Communication
  • Year:
  • 2012

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Abstract

We propose a source rate control scheme for streaming video sequences over wireless channels by resorting on a reduced-reference (RR) quality estimation approach. It works as follows: the server extracts important features of the original video, which are coded and sent through the channel along with the video sequence and then exploited at the decoder to compute the actual quality; the observed quality is analyzed to obtain information on the impact of the source rate at the given system configuration; at the receiver, decisions are taken on the optimal source rate to be applied next at the encoder to maximize the quality as perceived at the user-side. The rate is adjusted on a per-window basis to compensate low-throughput periods with high-throughput periods so as to avoid abrupt video quality changes, which can be caused by sudden variations in the channel throughput. The use of the RR quality estimation represents the main novelty of the proposed work. This has the advantage of allowing the rate control to optimize the user-perceived video quality after all the streaming system impairments have affected the signal, including actual channel errors, playback buffer starvation occurrences and error concealment. This approach is new in this context, since in the past proposals video models are used to predict the relationships of the quality with the coding rate, channel errors and starvation occurrences. Numerical simulations show how the proposed approach is able to achieve results similar to those obtained with model-based approaches, but with the significant benefit of not requiring any knowledge on the signal and channel characteristics.