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Improved InSAR-BM3D Filtering Algorithm Based on Noise Variance Estimation
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DOI：10.1109/LGRS.2025.3646071.png)
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Abstract
En 中文
The conventional InSAR-BM3D filtering algorithm fails to accurately estimate noise variance in regions with low coherence and dense fringe patterns, resulting in inadequate noise suppression and loss of detailed features. To overcome this limitation, this letter proposes an improved InSAR-BM3D method that incorporates frequency-domain interferometric phase analysis. Specifically, the median absolute deviation (MAD) method is employed to estimate noise variance in target regions, and this optimized variance estimation is then integrated into the InSAR-BM3D filtering. To validate the effectiveness of the proposed method, both simulated and real-data experiments were conducted, with comparative analyses performed against wavelet threshold filtering, Goldstein filtering, NL-InSAR filtering, and conventional InSAR-BM3D filtering in terms of results and evaluation metrics. The experimental results demonstrate that: the improved method outperforms other approaches in noise suppression and detail preservation, exhibiting superior performance across quantitative metrics, including root mean square error (RMSE) and edge retention index (ERI); in the Mandalay region, the proposed method achieves 9.8%, 6.7%, and 12.8% improvements in phase standard deviation (PSD), number of residues (NOR), and sum of phase differences (SPDs), respectively, compared to original InSAR-BM3D filtering.
Keywords:
Filtering
Noise
Estimation
Coherence
Frequency-domain analysis
Three-dimensional displays
Filters
Indexes
Wiener filters
Maximum likelihood estimation
InSAR-BM3D filtering
interferometric synthetic aperture radar (InSAR)
median absolute deviation (MAD)
noise variance estimation
phase denoising
Journal
I
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4.4
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806
Citations:
0
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