کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
531296 | 869825 | 2011 | 15 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Hierarchical multispectral galaxy decomposition using a MCMC algorithm with multiple temperature simulated annealing Hierarchical multispectral galaxy decomposition using a MCMC algorithm with multiple temperature simulated annealing](/preview/png/531296.png)
We present a new method for the parametric decomposition of barred spiral galaxies in multispectral observations. The observation is modelled with a realistic image formation model and the galaxy is composed of physically significant parametric structures. The model also includes a parametric filtering to remove non-desirable aspects of the observation. Both the model and the filter parameters are estimated by a robust Monte Carlo Markov chain (MCMC) algorithm. The algorithm is based on a Gibbs sampler combined with a novel strategy of simulated annealing in which several temperatures allow to manage efficiently the simulation effort. Besides, the overall decomposition is performed following an original framework: a hierarchy of models from a coarse model to the finest one is defined. At each step of the hierarchy the estimate of a coarse model is used to initialize the estimation of the finer model. This leads to an unsupervised decomposition scheme with a reduced computation time. We have validated the method on simulated and real 5-band images: the results showed the accuracy and the robustness of the proposed approach.
Journal: Pattern Recognition - Volume 44, Issue 6, June 2011, Pages 1328–1342