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...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Remote sensing (Basel, Switzerland) Ročník 17; číslo 17; s. 3031
Hlavní autori:	Shen, Yan, Chen, Yazhou, Wang, Yuming, Ma, Liyun, Zhang, Xiaolu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.09.2025
Predmet:	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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!