InSAR interferogram filtering methods in the contourlet domain

Chuanguang Zhu; Hongdong Fan; Kazhong Deng; Jiqun Xue

doi:10.1117/12.912331

24 October 2011 InSAR interferogram filtering methods in the contourlet domain

Chuanguang Zhu, Hongdong Fan, Kazhong Deng, Jiqun Xue

Proceedings Volume 8286, International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications; 82860E (2011) https://doi.org/10.1117/12.912331
Event: International Symposium on Lidar and Radar Mapping Technologies, 2011, Nanjing, China

Abstract

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.

Citation Download Citation

Chuanguang Zhu, Hongdong Fan, Kazhong Deng, and Jiqun Xue "InSAR interferogram filtering methods in the contourlet domain", Proc. SPIE 8286, International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications, 82860E (24 October 2011); https://doi.org/10.1117/12.912331

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KEYWORDS

Discrete wavelet transforms

Interferometric synthetic aperture radar

Denoising

Wavelet transforms

Mining

Synthetic aperture radar

Visualization

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