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We consider a stationary symmetric stable bidimensional process with discrete time, having the spectral representation (1.1). We consider a general case where the spectral measure is assumed to be the sum of an absolutely continuous measure, a discrete measure of finite order and a finite number of absolutely continuous measures on several lines. We estimate the density of the absolutely continuous measure and the density on the lines.
The estimation of probabilistic deformable template models in
computer vision or of probabilistic atlases in Computational Anatomy
are core issues in both fields.
A first coherent statistical framework where the geometrical variability is
modelled as a hidden
random variable has been
given by [S. Allassonnière et al., J. Roy. Stat. Soc.69 (2007) 3–29]. They introduce
a Bayesian approach and
mixture of them to estimate deformable template models.
A consistent stochastic algorithm has been introduced...
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