Model-based low bit-rate video coding for resource-deficient wireless visual communication

In this paper, an effective low bit-rate video coding scheme is developed to realize state-of-the-art video coding efficiency with lower encoder complexity, while supporting standard compliance and error resilience. Such an architecture is particularly attractive for application scenarios involving resource-deficient wireless video communications. At the encoder, in order to increase resilience to channel error, multiple descriptions of a video sequence are generated in the spatio-temporal domain by temporal multiplexing and spatial adaptive downsampling. The resulting side descriptions are interleaved with each other in temporal domain, while still with conventional square sample grids in spatial domain. As such, each side description can be compressed without any change to existing video coding standards. At the decoder, each side description is first decompressed, and then reconstructed to the original resolution with the help of the other side description. In this procedure, the decoder recovers the original video sequence in a constrained least squares regression process, in which 2D or 3D piecewise autoregressive model is adaptively chosen according to different predictive modes. In this way, the spatial and temporal correlation is sufficiently explored to achieve superior quality. Experimental results demonstrate that the proposed video coding scheme outperforms H.264/AVC and other state-of-the-art methods in rate–distortion performance at low bit-rates and achieves superior visual quality at medium bit rates as well, while with lower encoding computational complexity.