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
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.