|Title||Towards random field modeling of wavelet statistics|
|Publication Type||Conference Paper|
|Year of Publication||2002|
|Authors||Azimifar, Z., P. Fieguth, and E. Jernigan|
|Conference Name||International Conference on Image Processing|
|Conference Location||Rochester, NY|
|Keywords||image characterization, image processing, Markov processes, Markov random field modeling, MRF, signal characterization, statistical analysis, statistical image processing, wavelet statistics, wavelet transforms|
The paper investigates the statistical characterization of signals and images in the wavelet domain. 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. We investigate possible choices of statistical-interaction models. One efficient and fast strategy which describes the wavelet-based statistical correlations is illustrated. Finally, the effectiveness of the proposed tool towards an efficient hierarchical MRF (Markov random field) modeling of within-scale neighborhoods and across-scale dependencies is demonstrated.