IEEE International Conference on Acoustics, Speech, & Signal Processing, May 2001


Rate Scalable Video Coding Using A Foveation-Based Human Visual System Model

 Zhou Wang1, Ligang Lu2, and Alan C. Bovik1

1 Laboratory for Image and Video Engineering (LIVE), Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712-1084

2 IBM T. J. Watson Research Center, Yorktown Heights, NY 10598

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Abstract: Recently, there are two interesting trends in image and video coding research. One is to use human visual system (HVS) models to improve the current state-of-the-art coding algorithms by better exploiting the properties of the intended receiver. The other is to design rate scalable video codecs, which allow the extraction of coded visual information at continuously varying bit rates from a single compressed bitstream. In this paper, we follow these two trends and propose a foveation scalable video coding (FSVC) algorithm, which supplies good quality-compression performance as well as effective rate scalability to support simple and precise bit rate control. A foveation-based HVS model plays a key role in the algorithm. The algorithm is amenable to the inclusion of various HVS models and adaptable to different video communication applications.