Wavelet-based statistical signal processing using hidden Markovmodels
IEEE Transactions on Signal Processing
Bayesian tree-structured image modeling using wavelet-domain hidden Markov models
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
This paper presents a multiscale-based analysis of the statistical dependencies between the wavelet coefficients of random fields. In particular, in contrast to common decorrelated-coefficient models, we find that the correlation between wavelet scales can be surprisingly substantial, even across several scales. In this paper we investigate eight possible choices of statistical-interaction models, from trivial models to wavelet-based hierarchical Markov stochastic processes. Finally, the importance of our statistical approach is examined in the context of Bayesian estimation.