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A Fast Non‐Local Means Filtering Method for Interferometric Phase Based on Wavelet Packet Transform
Author(s) -
Yan Zhan,
Yan Hang,
Wang Tao
Publication year - 2021
Publication title -
radio science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 84
eISSN - 1944-799X
pISSN - 0048-6604
DOI - 10.1029/2019rs007052
Subject(s) - wavelet packet decomposition , wavelet , wavelet transform , computer science , transformation (genetics) , algorithm , interferometry , discrete wavelet transform , filter (signal processing) , phase (matter) , second generation wavelet transform , stationary wavelet transform , mathematics , artificial intelligence , computer vision , optics , physics , biochemistry , chemistry , quantum mechanics , gene
Phase unwrapping is very important to acquire surface deformation using InSAR, unwrapping the interferometric phase directly is not appropriate because the phase is affected by various noises. Therefore, it is essential to apply a suitable filter to the interferometric phase before phase unwrapping. Although there are many filtering methods for noise, these methods cannot be used directly due to the particularity of interferometric phase noise and therefore it is important to do the corresponding domain transformation. Here, a fast non‐local means filtering method based on wavelet packet transform is proposed. Originally, wavelet packet transform is performed on the real part and the imaginary part respectively, which avoids the influence of phase jumps on the subsequent filtering. Furthermore, the fast non‐local means filtering can be applied to smooth the acquired wavelet packet coefficients. Eventually, inverse transform of the wavelet packet is used to reconstruct the phase after filtering. Compared with other filtering algorithms in simulated and actual Sentinel‐1 data, the superiority of this algorithm is proved.