conventional source coding, a single encoder exploits the correlation of
the source to perform compression. Many applications, however, involve multiple
sources often separated in space that need to be compressed independently.
Distributed source coding therefore studies the problem of compressing such
sources in a distributed fashion. Distributed
source coding finds application in sensor networks, low-complexity video
encoding, compression of multi-view images and multi-view videos.
Our main interest is in developing new distributed
compression algorithms for compression of multi-view images or video sequences.
We are exploring the use of quad-tree decomposition algorithms and extensions
of the wavelet transform to develop new distributed image or video compression schemes.
Our algorithms are tested using the multicamera system shown in Fig 1 and
sponsored by Royal Society and Selex.
Fig. 1. Our multiview
camera system sponsored by the Royal Society and Selex.
achieve distributed compression of multi-view images, we developed a
quad-tree based compression algorithm. In our approach some images are
compressed using this algorithm and the full information is
transmitted, for other images only partial information of the quadtree
structure and of the leaf content is transmitted. The receiver
estimates the missing information by decoding the information received
Collaborations and Interactions:
M. Vetterli (EPFL) and K. Ramchandran (UC, Berkeley)