In this paper a new class of random field, defined on a multiresolution array structure, is described. Some of the fundamental statistical properties of the model are established. Estimation from noisy data is then considered and a new procedure, multiresolution maximum a posteriori estimation, is defined. These ideas are then applied to the problem of segmenting images containing a number of regions. Implementation of the Bayesian approach is based on a multiresolution form of Gibbs sampling. It is shown that the model forms an excellent basis for the segmentation of such images, which works with no a priori information on the number or sizes of the regions.
|Title of host publication||Proceedings - International Conference on Image Analysis and Processing, ICIAP 1999|
|Number of pages||6|
|Publication status||Published - 1999|
|Event||10th International Conference on Image Analysis and Processing, ICIAP 1999 - Venice, Italy|
Duration: 27 Sep 1999 → 29 Sep 1999
|Conference||10th International Conference on Image Analysis and Processing, ICIAP 1999|
|Period||27/09/99 → 29/09/99|