The Wishart classifier has the major issue of drastically favoring the intensity over the polarimetric information

so the weak backscattering targets such as water

road

bare soil and shadow in Polariemtric Synthetic Aperture Radar（PolSAR） image are hard to be made fine distinction.This paper proposed an unsupervised statistical classifier of the weak backscattering scatterers based on H-α target decomposition and hypothesis test.Likelihood ratio test is used as a distance measure to compare the similarity of a pixel and class centers.Pixels with small similarity are rejected according to the first type error and the distribution of the test statistics to reduce the effect on classification.The others pixels being not rejected are assigned to the class with the smallest statistics.The experiential results using E-SAR L band and Radarsat-2 C band quad polarimetric image demonstrate that this algorithm making advantage of the polarimetric information

improves the classification accuracy of the weak backscattering scatterers greatly.