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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE geoscience and remote sensing letters 2020-12, Vol.17 (12), p.2100-2104
Hauptverfasser: Maji, Suman Kumar, Thakur, Ramesh Kumar, Yahia, Hussein M.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
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.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2019.2963453