Abstract: To obtain accurate segmentation of polarimetric SAR images in different heterogeneity areas, a new segmentation method is proposed in this paper which selectively uses Wishart and K statistical description based on the fractal network evolution algorithm (FNEA). Specifically, initial objects are derived by using superpixels efficiently generated by simple linear iterative clustering (SLIC) algorithm. Similarity criterion between adjacent objects is defined by Wishart and K distribution depending on the regional heterogeneity index. Then the segmentation procedure for polarimetric data is realized, which makes full use of Wishart and K statistical description. Moreover, simulated data and real data are used to verify the effectiveness of the proposed method. The experiment result shows it can accurately segment different heterogeneity areas on the whole and get more precise boundary in the local details compared with other algorithms.