An Absolute Phase Estimation Method for Interferometry Imagery

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Sui Ping Lee
Yee Kit Chan
Tien Sze Lim

Abstract

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2?-periodic phase image that wrapped within (-?, ?]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.

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References

[1] A. R. Thompson, J. M. Moran and G. W. Swenson, “ Introductory Theory of Interferometry and Synthesis Imaging,” Astronomy and Astrophysics Library, pp. 59-88, 2017.
[2] S. Lian and H. Kudo, “Phase Unwrapping with Differential Phase Image,” Medical Imaging 2017: Physics of Medical Imaging, doi:10.1117/12.2255727, 2017.
[3] H. Hongxing, J. M. Bioucas-Dias and V. Katkovnik, “Interferometric Phase Image Estimation via Sparse Coding in the Complex Domain,” IEEE Trans. Geosci. Remote Sensing, vol. 53, no.5, pp. 2587-2602, 2015.
[4] M. Shimada, “SAR Interferometry,” Imaging from Spaceborne and Airborne SARs, Calibration, and Applications, pp. 251-302, 2018.
[5] J. Dong, F. Chen, D. Zhou, T. Liu, Z. Yu and Y. Wang, “Phase Unwrapping with Graph Cuts Optimization and Dual Decomposition Acceleration for 3D High-resolution MRI Data,” Magnetic Resonance in Medicine, vol. 77, no.3, pp. 1353-1358, 2016.
[6] C. Tian and S. Liu, “Phase Retrieval in Two-shot Phase-shifting Interferometry based on Phase Shift Estimation in A Local Mask,” Optics Express, vol. 25, no.18, pp. 21673-21683, 2017.
[7] G. Franceschetti and R. Lanari, “Synthetic Aperture Radar Interferometry,” Synthetic Aperture Radar Processing, doi:10.1201/9780203737484-4, pp.167-223, 2018.
[8] P. A. Rosen, S. Hensley, I. R. Joughin, S. N. Madsen, E. Rodriguez and R. M. Goldstein, “Synthetic Aperture Radar Interferometry,” Proceedings of the IEEE, vol. 88, no. 2, pp. 333-382, 2000.
[9] D. C. Ghighlia and M. D Pritt, Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software, New York, Wiley-Interscience, 1998.
[10] H. A. Zebker and Y. P. Lu, “Phase Unwrapping Algorithms for Radar Interferometry—Residue-cut, Least-squares and Synthesis Algorithms,” J. Opt. Soc. Amer. A, vol. 15, no. 3, pp. 586–598, 1998.
[11] J. S. Lee, K. Hoppel, S. Mango and A. Miller, “Intensity and Phase Statistics of Multilook Polarimetric and Interferometric SAR Imagery,” IEEE Trans. Geosci. Remote Sensing, vol. 32, no. 5, pp. 1017-1028, 1994.
[12] J. S. Lee, K. Papathanassiou, T. Ainsworth, M. Grunes and A. Reigber, “A New Technique for Noise Filtering of SAR Interferometric Phase Images,” IEEE Trans. Geosci. Remote Sensing, vol. 36, no. 5, pp. 1456-1465, 1998.
[13] H. Zebker and J. Villasenor, “Decorrelation in Interferometric Radar Echoes,” IEEE Trans. Geosci. Remote Sensing, vol. 30, no. 5, pp. 950-959, 1992.
[14] S. Mukherjee, A. Zimmer, X. Sun, P. Ghuman and I. Cheng, “CNN-based InSAR Coherence Classification,” 2018 IEEE Sensors, doi:10.1109/icsens.2018.8589742, 2018.