Structure-Preserving Denoising of SAR Images Using Multifractal Feature Analysis
In this letter, we propose a speckle removal denoising algorithm for synthetic aperture radar (SAR) images. The approach is based on the concept of extracting informative feature (based on the concept of multifractal decomposition of signals) from a speckle-induced SAR image and then estimating a no...
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Veröffentlicht in: | IEEE geoscience and remote sensing letters 2020-12, Vol.17 (12), p.2100-2104 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In this letter, we propose a speckle removal denoising algorithm for synthetic aperture radar (SAR) images. The approach is based on the concept of extracting informative feature (based on the concept of multifractal decomposition of signals) from a speckle-induced SAR image and then estimating a noise-free image from the gradients restricted to those features. The experimental results show that the proposed technique not only improves the visual quality of the SAR images but also effectively preserves their texture. Comparison with the classical and state-of-the-art denoising techniques shows the advantages of the proposed scheme, both visually and quantitatively. |
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ISSN: | 1545-598X 1558-0571 |
DOI: | 10.1109/LGRS.2019.2963453 |