Scalable Foveated Visual Information 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.

[1]  Ya-Qin Zhang,et al.  Robust video coding algorithms and systems , 1999 .

[2]  Zhou Wang,et al.  Foveation scalable video coding with automatic fixation selection , 2003, IEEE Trans. Image Process..

[3]  A. Bovik,et al.  A universal image quality index , 2002, IEEE Signal Processing Letters.

[4]  Wilson S. Geisler,et al.  Real-time foveated multiresolution system for low-bandwidth video communication , 1998, Electronic Imaging.

[5]  William A. Pearlman,et al.  A new, fast, and efficient image codec based on set partitioning in hierarchical trees , 1996, IEEE Trans. Circuits Syst. Video Technol..

[6]  Marios S. Pattichis,et al.  Foveated video compression with optimal rate control , 2001, IEEE Trans. Image Process..

[7]  John D. Villasenor,et al.  Visibility of wavelet quantization noise , 1997, IEEE Transactions on Image Processing.

[8]  Zhou Wang,et al.  Adaptive frame prediction for foveation scalable video coding , 2001, IEEE International Conference on Multimedia and Expo, 2001. ICME 2001..

[9]  Alan C. Bovik,et al.  Real-time foveation techniques for low bit rate video coding , 2003, Real Time Imaging.

[10]  Edward J. Delp,et al.  Wavelet based rate scalable video compression , 1999, IEEE Trans. Circuits Syst. Video Technol..

[11]  Zhou Wang,et al.  Wavelet-based foveated image quality measurement for region of interest image coding , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[12]  Huifang Sun,et al.  Architectures for MPEG compressed bitstream scaling , 1996, IEEE Trans. Circuits Syst. Video Technol..

[13]  Ming-Ting Sun,et al.  CHAPTER 9 – MPEG-1 and MPEG-2 Video Standards , 1999 .

[14]  Shih-Fu Chang,et al.  A highly efficient system for automatic face region detection in MPEG video , 1997, IEEE Trans. Circuits Syst. Video Technol..

[15]  Alan C. Bovik,et al.  Visual pattern image sequence coding , 1993, IEEE Trans. Circuits Syst. Video Technol..

[16]  Jerome M. Shapiro,et al.  Embedded image coding using zerotrees of wavelet coefficients , 1993, IEEE Trans. Signal Process..

[17]  Eric L. Schwartz,et al.  Computational anatomy and functional architecture of striate cortex: A spatial mapping approach to perceptual coding , 1980, Vision Research.

[18]  G.J. Minden,et al.  A survey of active network research , 1997, IEEE Communications Magazine.

[19]  Zhou Wang,et al.  Embedded foveation image coding , 2001, IEEE Trans. Image Process..