A novel technique for image segmentation with Markov chain model

With the consideration of the multi-component representation of an hyperspectral data cube, the hidden Markov chain (HMC) model has been extended parameters estimation is performed using the general iterative conditional estimation (ICE) method. The vectorial extension of the model is straightforward since the vectorial point of view joints the observation of each pixel as a spectral signature. Then, the segmentation procedure achieves an estimation of multi-dimensional correlated probability density functions (pdf). Multi-dimensional densities have been estimated by a set of ID densities through a projection step that makes component independent and of reduced dimension