The Comparison of the V-Fold and the Monte-Carlo cross validation to estimate the number of clusters for the fully polarimetric sar data segmentation

In this paper, the cross validation algorithm is used to estimate the number of clusters for the unsupervised classification of fully polarimetric SAR data. Three different cross validation algorithms are applied for comparison, which are the dispersion measure method, the V-fold cross validation (VFCV) and the Monte-Carlo cross validation (MCCV). Our current experiments show that the dispersion measure method appears generally unable to provide a reliable estimation. The VFCV and the MCCV algorithms seem to be more effective than the dispersion measure method. Moreover, the VFCV is much faster than the MCCV, but the MCCV may be able to provide better estimation than the VFCV.