Wyner-Ziv based video codecs reverse the
processing complexity between encoders and decoders
such that the complexity of the encoder can be
significantly reduced at the expense of highly complex
decoders requiring hardware accelerators to achieve
real time performance. In this paper we describe a
flexible hardware architecture for processing the
Belief Propagation algorithm in a real time Wyner-Ziv
video decoder for several hundred, very large, Low
Density Parity Check (LDPC) codes. The proposed
architecture features a hierarchical memory structure
to provide a caching capability to overcome the high
memory bandwidths needed to supply data to the
processors. By taking advantage of the deterministic
nature of LDPC codes to increase cache utilization, we
are able to substantially reduce the size of expensive,
high speed memory needed to support the processing
of large codes compared to designs implementing a
single layer memory structure.
We analyze challenges in the current approaches to digital video surveillance solutions, both technically and financially.
We propose a Cell Processor based digital video surveillance platform to overcome those challenges and address ever
growing needs in enterprise class surveillance solutions capable of addressing multiple thousands camera installations.
To improve the compression efficiency we have chosen H.264 video compression algorithm which outperforms all
standard video compression schemes as of today.