Initialization of Markov Random Field clustering of large polarimetric SAR images

Markov Random Field clustering, utilizing both spectral and spatial inter-pixel dependency information, often provides higher accuracy for remote sensing images, such as polarimetric SAR images. However, it is heavily sensitive to initial conditions, i.e. the initialization of parameters and the choice of the number of clusters. In this paper, an initialization scheme for MRF clustering approaches for polarimetric SAR images is suggested. The method takes into account spatial relations between pixels and provides a guideline to the choice of the number of clusters using Pseudolikelihood Information Criterion (PLIC) criterion. A well-known polarimetric SAR image of Flevoland in the Netherlands is given as an example, showing that this approach gives very good performance.