Multiaspect Synthetic Aperture Radar (SAR) can generate high resolution images and target scattering signatures in different azimuth angles from the coherent integration of all subaperture images. However, mixed anisotropic scatters limit the application of traditional imaging theory. Anisotropic scattering may introduce errors in polarimetric parameters by decreasing the reliability of terrain classification and detection of variability. Thus a method is proposed for estimating and removing anisotropic scattering in multiaspect polarimetric SAR images. The proposed algorithm is based on the maximum likelihood and likelihood-ratio tests for the two-class case, while considering the speckle effect, the mechanism of removing the anisotropic scattering, and the monotonicity of the Constant False Alarm Rate (CFAR) detection function. We compare the polarimetric entropy before and after removing the anisotropic subapertures, and then validate the algorithm's potential in retrieving the target signature using a P-band quad-pol airborne SAR with circular trajectory.