Human visual system based scalable video coding and communications

This paper introduces our recent research work on the development of a scalable foveated visual information coding and communication system, which follows two emerging trends in visual communication research. One is to design rate scalable image and video codecs, which allow the extraction of coded visual information at continuously varying bit rates from a single compressed bitstream. The other is to incorporate human visual system models to improve the state-of-the-art of image and video coding techniques by better exploiting the properties of the intended receiver. The central idea of the proposed system is to organize the encoded bitstream to provide the best decoded visual information at an arbitrary bit rate in terms of foveated visual quality measurement. Such a scalable foveated visual information processing system has many potential applications in the field of visual communications. Significant examples include network image browsing, network videoconferencing, robust visual communication over noisy channels, and visual communication over active networks.