DATNet: Dynamic Adaptive Transformer Network for SAR Image Denoising

Aiming at the problems of detail blurring and structural distortion caused by speckle noise, additive white noise and hybrid noise interference in synthetic aperture radar (SAR) images, this paper proposes a Dynamic Adaptive Transformer Network (DAT-Net) integrating a dynamic gated attention module...

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Bibliographic Details
Published in:	Remote sensing (Basel, Switzerland) Vol. 17; no. 17; p. 3031
Main Authors:	Shen, Yan, Chen, Yazhou, Wang, Yuming, Ma, Liyun, Zhang, Xiaolu
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.09.2025
Subjects:	Artificial satellites in remote sensing attention encoder–decoder network Design Efficiency Electric transformers Embedding Feature extraction Fourier transforms Frequency dependence Frequency domain analysis Heterogeneity image denoising Innovations Learning strategies Medical imaging equipment Methods Modules Noise Noise reduction Parameter estimation Radar imaging Spatial heterogeneity Synthetic aperture radar Transformer Wavelet transforms White noise
ISSN:	2072-4292, 2072-4292
Online Access:	Get full text
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