Welcome to Xiaoyi's homepage.
I'm a second year grad student in EECS department at UC Berkeley. I'm
working toward my Master's degree under the supervision of Prof. Avideh
Zakhor. This work is supported by NSF Grant ANI 9997442.
My current research project is multiple description coding (MDC).
MDC is an error resilient source coding scheme
that creates multiple bitstreams of approximately equal importance.
The reconstructed signal based on any single bitstream has an
acceptable quality. However, a higher quality reconstruction can be achieved
with larger number of bitstreams.
We develop a multiple (2) description video coding scheme based on the
3 loop structure originally proposed in .
We modify the discrete cosine transform structure to the matching pursuit
framework and evaluate performance gain using maximum likelihood (ML)
enhancement when both descriptions are available.
We find that ML enhancement works best for low motion
sequences and results in gains of up to 1.3 dB in terms of average PSNR.
Rate distortion performance is characterized.
Performance comparison is made between our MDC scheme and
single description coding
(SDC) schemes over
lossy channels, including two state Markov channels
and Rayleigh fading channels.
We find that MDC outperforms SDC in bursty slowly varying environments.
In the case of Rayleigh fading channels,
interleaving helps SDC close the gap
and even outperform MDC depending on the amount of interleaving
performed, at the expense of additional delay.
 A. Reibman, Y. Wang, M. Orchard, and R. Puri, "Multiple description coding
for video using motion compensated prediction," in Proc. ICIP 99, pp. 837-841,
last updated: 2/10/2001