Polarimetric Synthetic Aperture Radar（ SAR） data record an increased amount of scattering information of ground targets with fully polarimetric patterns. Thus

polarimetric SAR has become a key issue in development. Polarimetric SAR technologies have made significant progress in applications such as military and civil remote sensing. However

because of the limitation of coherent imaging

speckle in SAR and polarimetric SAR data seriously affects the relative information extraction. Therefore

speckle suppression is an important step in SAR and polarimetric SAR data processing. Subsequent applications with polarimetric SAR data could be supported. The Bilateral Filter（ BF） that combines spatial closeness and gray similarity to suppress speckle is an excellent edge preservation filtering algorithm. This paper proposes an Improved Cross Bilateral Filter（ ICBF） to resolve the deficiency of the BF in speckle suppression of polar metric SAR data. The reference image was imported to improve the gray similarity measurement accuracy of the original data

and a new strategy that sets two key parameters of bilateral filter based on the variance coefficient of filter window was presented to adapt to the change in the homogeneity degree of the filter window. The ICBF added scattering mechanism measurement to extend the original weight kernel

adjusted spatial closeness variance via the local coefficient of variation by using SPAN image

and measured the similarity of gray value and scattering mechanism by using a reference image.The experiment was conducted with AIRSAR polar metric data in the San Francisco region. The proposed filter algorithm was then compared with classic filter algorithms

such as Boxcar

IDAN

and Refined Lee

based on speckle suppression

detailed information preservation

scattering and polarization information preservation with the visual and index methods. The experimental results show that ICBF could improve the gray similarity measurement accuracy of the original data and that ICBF can suppress speckle and preserve detailed information

such as point targets and edges in the original data

better than the classic filter algorithms. By contrast

the measurement of scattering mechanism was combined in the kernel function of bilateral filter

the parameter of the space distance weight was obtained from SPAN image

and the weights of gray value and scattering mechanism were measured with the standard deviation of the corresponding data. Thus

the polarization information and scattering characteristics of the original data were preserved well. Compared with classic filtering algorithms

the ICBF can smooth noise and preserve detailed information better. Furthermore

polarization information and scattering characteristics of the original data are maintained to support subsequent application based on polarimetric SAR data.