Project: Vector Set Partitioning for Image and Video Coding

PEOPLE

Debargha Mukherjee, S.K.Mitra

OBJECTIVE

The wavelet transform, in conjunction with zero tree quantization techniques has recently been shown to be very efficient for natural image compression. In this project, a generic framework for embedded vector zero tree coding, called Vector Set-Partitioning in Hierarchical Trees (VSPIHT), has been developed. Here the individual coding units are vectors rather than scalars. Wavelet coefficients grouped as vectors, are classified by the set-partitioning methodology, and successively refined using training or lattice vector quantization (VQ) techniques. Efficient compression schemes using VSPIHT methodology have been developed for monochrome and color images, as well as for color video. In all cases, an embedded bitstream is generated allowing functionalities such as SNR scalability, and progressive transmissibility. Since VSPIHT works well especially for images and parts of images with a great deal of detail, multimode VSPIHT can effectively alter the balance of bits in the mixed VSPIHT bit-stream so that much fewer critical bits carrying significance information are produced. This makes the use of unequal error protection for transmission of images over a noisy channel particularly convenient. Two generic methodologies for successive refinement of vectors, applicable to all kinds of embedded coding have been investigated. The first has lead to the development of Voronoi Lattice VQs for successive refinement of uniformly distributed vectors, and the second aims at developing new constrained storage multistage VQ structures allowing fine tradeoffs between storage and efficiency. The results of various parts of this project have been presented at national and international con­ferences [2-9], and have appeared in a journal [1]. 

PUBLICATIONS

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1. Debargha Mukherjee, and Sanjit K. Mitra, "On the robustness of vector set partitioning image coders to channel errors" Proceedings of the IEEE International Symposium on Circuits and Systems , Orlando, Florida, June 1999.

2. D. Mukherjee and S.K. Mitra, "Generalized variable dimensional set partitioning for embedded wavelet image compression," Proc. IEEE International Conference on Acoustics , Speech & Signal Processing, Phoenix, AZ, March 1999.

3. D. Mukherjee and S.K. Mitra, "Arithmetic coded vector SPIHT with classified tree multistage VQ for color image coding," Proc. IEEE  Workshop on Multimedia Signal Processing , Los Angeles, CA, December 1998, pp. 444-449.

4. D. Mukherjee and S.K. Mitra, "Vector set-partitioning with successive refinement Voronoi lattice VQ for embed­ded wavelet image coding," Proc. IEEE International Conference on Image Processing , Part I, Chicago, IL, October 1998, pp. 107-111  - Winner of the Best Student Paper Award.

5. D. Mukherjee and S.K. Mitra, "A vector set partitioning noisy channel image coder with un­equal error protection," IEEE J. on Selected Areas in Communications , Special Issue on Error-Resilient Image and Video Communication, vol. 18, June 2000, pp. 829-840.

6. D. Mukherjee, J.J. Chae, and S.K. Mitra, "A source and channel coding approach to data hiding with application to hiding speech in video," Proc. IEEE International Conference on Image Processing , Part I, Chicago, IL, October 1998, pp. 348-352.

7. D. Mukherjee and S.K. Mitra, "Vector set partitioning with classified successive re­finement VQ for embedded Wavelet image coding," Proc. IEEE International Symposium on Circuits & Systems , Monterey, CA, June 1998, pp. 25-28.

8. D. Mukherjee and S.K. Mitra, "Vector set partitioning with classified successive re­finement VQ for embedded wavelet image and video coding," Proc. IEEE International Conference on Acoustics, Speech & Signal Processing , Seattle, WA, May 1998, pp. 2809-2812.

9. D. Mukherjee and S.K. Mitra, " Region based video coder using edge flow segmentation and hierarchical affine region matching," Proc. SPIE Conference on Visual Communications and Image Processing , vol. 3309, San Jose, CA, January 1998.