The interferogram contains much noise which reduce the precision when phase unwrapping. In this paper, we filter the
interferogram in the contourlet domain. The contourlet transform (CT) has flexible aspect ratios and can effectively
capture geometry information of interferogram edges. However, the CT is lack of the feature of translation invariance.
Hereby we study the cycle-spinning CT (CSCT) to convert the commonly CT to translation invariance. Firstly, we
translate the original interferogram before being decomposed. Secondly, we decompose the translated interferogram
using the CT, and modify the coefficients. Finally, we reconstructed the interferogram with the modified coefficients and
translate back. In the experimentation, the data is selected both from the plain and mountain area. The results show that
the CSCT outperform the discrete wavelet transform (DWT), the CT in terms of the residues number and the mean value
of the correlation coefficient. In texture retrieval, the CSCT shows improvements in performance for various oriented
texture and the results indicate a better compromise between noise removal and the detail preservation. Besides, in the
mountain area, the CSCT performed well than in the plain area because there is more texture in the mountain area.