A probabilistic approach for rate-distortion modeling of multiscale binary shape

Anthony Vetro, Yao Wang, Huifang Sun

Research output: Contribution to journalArticlepeer-review

Abstract

The purpose of this paper it to explore the relationship between the rate-distortion (R-D) characteristics of multiscale binary shape and Markov Random Field (MRF) parameters. In our experiments, we consider two prior models. The first MRF model takes into account pair-wise interaction between pels, and for the binary case, is typically referred to as the auto-logistic model; the second MRF model accounts for higher order spatial interactions and is referred to as the Chien model. Experimental results indicate that the autologistic model is not sufficient to characterize the R-D characteristics of multiscale binary shape data. However, higher order models, such as the Chien model, do seem feasible. We propose to use the statistical moments of the Chien model as input to a neural network to accurately predict the rate and distortion of the binary shape when coded at various scales.

Original languageEnglish (US)
Pages (from-to)3353-3356
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
DOIs
StatePublished - 2002

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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