A large number of practical coding scenarios deal with sources such as transform coefficients that can be well modeled as Laplacians. For regular coding of such sources, samples are often quantized by a family of uniform quantizers possibly with a deadzone, and then entropy coded. For the Wyner-Ziv coding problem when correlated side-information is available at the decoder, the side-information can be modeled as obtained by additive Laplacian or Gaussian noise on the source. This paper deals with optimal choice of parameters for practical Wyner-Ziv coding in such scenarios, using the same quantizer family as in the regular codec to cover a range of rate-distortion trade-offs, given the variances of the source and additive noise. We propose and analyze a general encoding model that combines source coding and channel coding and show that at practical block lengths and code complexities, not pure channel coding but a hybrid combination of source coding and channel coding with right parameters provide optimal rate-distortion performance. Further, for the channel coded bit-planes we observe that only high-rate codes are useful. We also provide a framework for on-the-fly parameter choice based on non-parametric representation of a set of seed functions, for use in scenarios where variances are estimated during encoding. A good understanding of the optimal parameter selection mechanism is essential for building practical distributed codecs. Publication Info: To be published and presented at Proceedings of SPIE/Visual Communications and Image Processing, San Jose Jan 2008. 12 Pages
PDF
download
878987797
028-85220240
