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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Veröffentlicht in:	Remote sensing (Basel, Switzerland) Jg. 17; H. 17; S. 3031
Hauptverfasser:	Shen, Yan, Chen, Yazhou, Wang, Yuming, Ma, Liyun, Zhang, Xiaolu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.09.2025
Schlagworte:	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
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Abstract	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 and a frequency-domain multi-expert enhancement module for SAR image denoising. The proposed model leverages a multi-scale encoder–decoder framework, combining local convolutional feature extraction with global self-attention mechanisms to transcend the limitations of conventional approaches restricted to single noise types, thereby achieving adaptive suppression of multi-source noise contamination. Key innovations comprise the following: (1) A Dynamic Gated Attention Module (DGAM) employing dual-path feature embedding and dynamic thresholding mechanisms to precisely characterize noise spatial heterogeneity; (2) A Frequency-domain Multi-Expert Enhancement (FMEE) Module utilizing Fourier decomposition and expert network ensembles for collaborative optimization of high-frequency and low-frequency components; (3) Lightweight Multi-scale Convolution Blocks (MCB) enhancing cross-scale feature fusion capabilities. Experimental results demonstrate that DAT-Net achieves quantifiable performance enhancement in both simulated and real SAR environments. Compared with other denoising algorithms, the proposed methodology exhibits superior noise suppression across diverse noise scenarios while preserving intrinsic textural features.
AbstractList	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 and a frequency-domain multi-expert enhancement module for SAR image denoising. The proposed model leverages a multi-scale encoder–decoder framework, combining local convolutional feature extraction with global self-attention mechanisms to transcend the limitations of conventional approaches restricted to single noise types, thereby achieving adaptive suppression of multi-source noise contamination. Key innovations comprise the following: (1) A Dynamic Gated Attention Module (DGAM) employing dual-path feature embedding and dynamic thresholding mechanisms to precisely characterize noise spatial heterogeneity; (2) A Frequency-domain Multi-Expert Enhancement (FMEE) Module utilizing Fourier decomposition and expert network ensembles for collaborative optimization of high-frequency and low-frequency components; (3) Lightweight Multi-scale Convolution Blocks (MCB) enhancing cross-scale feature fusion capabilities. Experimental results demonstrate that DAT-Net achieves quantifiable performance enhancement in both simulated and real SAR environments. Compared with other denoising algorithms, the proposed methodology exhibits superior noise suppression across diverse noise scenarios while preserving intrinsic textural features.
Audience	Academic
Author	Ma, Liyun Shen, Yan Wang, Yuming Chen, Yazhou Zhang, Xiaolu
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Cites_doi	10.1109/TGRS.2024.3384953 10.1117/1.3600632 10.3390/rs16040656 10.1109/TGRS.2020.2993319 10.1109/ICACCAF.2016.7748978 10.1109/JSTARS.2024.3355220 10.1109/JSTARS.2021.3132027 10.3390/rs10020196 10.3390/rs12061006 10.3390/rs11131532 10.1109/TGRS.2023.3323485 10.1109/IGARSS52108.2023.10282914 10.1109/TIP.2003.819861 10.1016/S0146-664X(81)80018-4 10.1109/PROC.1981.11935 10.3390/rs11242921 10.1109/TGRS.2024.3489212 10.1109/CVPR52688.2022.00564 10.1109/IGARSS46834.2022.9884596 10.1109/JSTARS.2023.3292325 10.1109/ICPR.2010.579 10.1109/LSP.2017.2758203 10.1007/s11042-023-17468-2 10.1109/JPROC.2017.2675998 10.1109/LGRS.2024.3386020 10.3390/rs15235462 10.1109/IGARSS.2017.8128234 10.1109/TIP.2009.2029593 10.1007/s11831-021-09548-z 10.1016/j.engappai.2023.106444 10.1109/TPAMI.1985.4767641 10.1007/s00500-022-07522-w 10.1109/IRASET60544.2024.10549456 10.1088/1361-6501/acd1a6 10.3390/electronics14101950 10.1007/s12517-020-06416-1 10.1109/TGRS.2025.3572706 10.1109/ACCESS.2020.2965173 10.1007/978-3-031-78354-8_29 10.1109/ICTC55196.2022.9952991 10.1080/01431161.2023.2277167 10.1117/1.JEI.32.2.021609 10.1007/s11042-023-17648-0 10.1109/TIP.2007.901238 10.3390/rs15020330 10.1016/j.rse.2022.113369 10.11834/jrs.20220296 10.1109/TGRS.2023.3314857 10.1007/s10278-023-00842-9 10.3390/rs15020308 10.3390/electronics12224595 10.1109/TIP.2007.891788 10.1109/TGRS.2024.3397325 10.3390/rs15071860 10.1109/TIP.2017.2662206 10.3390/s23146342 10.1109/RADAR58436.2024.10993737 10.1109/JSTARS.2021.3071864
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References	ref_50 Yang (ref_44) 2025; 63 Li (ref_51) 2024; 62 ref_14 ref_12 ref_55 Yasir (ref_2) 2023; 27 Cheng (ref_57) 2017; 105 Shen (ref_66) 2020; 59 ref_59 Frost (ref_19) 1981; 69 Du (ref_56) 2025; 63 Yuan (ref_54) 2023; 36 Mao (ref_11) 2024; 62 ref_61 Gu (ref_47) 2020; 8 Lin (ref_31) 2023; 16 Zhang (ref_60) 2011; 20 Zhou (ref_3) 2024; 21 Singh (ref_15) 2021; 28 ref_25 Liu (ref_53) 2024; 62 Ko (ref_29) 2022; 15 ref_65 ref_20 ref_64 Parhad (ref_9) 2024; 83 ref_28 ref_27 Shan (ref_48) 2023; 34 Wu (ref_62) 2022; 26 Wang (ref_63) 2004; 13 Wessels (ref_5) 2023; 284 Singh (ref_16) 2022; 32 Dabov (ref_22) 2007; 16 Foi (ref_58) 2007; 16 Painam (ref_23) 2021; 14 ref_36 ref_35 ref_33 ref_32 ref_30 Wang (ref_10) 2024; 17 Lee (ref_17) 1981; 15 ref_39 Xiao (ref_37) 2024; 62 Kuan (ref_18) 1985; 7 Deledalle (ref_21) 2009; 18 Zhang (ref_46) 2017; 26 Yuan (ref_43) 2023; 61 Dalsasso (ref_49) 2021; 14 Yang (ref_13) 2024; 62 Wang (ref_26) 2017; 24 ref_41 ref_40 ref_1 Wang (ref_38) 2023; 21 Liu (ref_42) 2024; 62 Sivapriya (ref_34) 2023; 44 ref_8 Vitale (ref_52) 2023; 61 Zha (ref_45) 2023; 123 ref_4 ref_7 Jebur (ref_24) 2024; 83 ref_6
References_xml	– volume: 21 start-page: 4001205 year: 2023 ident: ref_38 article-title: A Practical SAR Despeckling Method Combining Swin Transformer and Residual CNN publication-title: IEEE Geosci. Remote Sens. Lett. – volume: 63 start-page: 5208013 year: 2025 ident: ref_44 article-title: RMSO-ConvNeXt: A Lightweight CNN Network for Robust SAR and Optical Image Matching Under Strong Noise Interference publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 62 start-page: 5210216 year: 2024 ident: ref_11 article-title: Radio Frequency Interference Mitigation in SAR Systems via Multi-Polarization Framework publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2024.3384953 – volume: 20 start-page: 023016 year: 2011 ident: ref_60 article-title: Color Demosaicking by Local Directional Interpolation and Nonlocal Adaptive Thresholding publication-title: J. Electron. Imaging doi: 10.1117/1.3600632 – ident: ref_1 doi: 10.3390/rs16040656 – volume: 59 start-page: 273 year: 2020 ident: ref_66 article-title: SAR image despeckling employing a recursive deep CNN prior publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2020.2993319 – ident: ref_7 doi: 10.1109/ICACCAF.2016.7748978 – volume: 17 start-page: 4036 year: 2024 ident: ref_10 article-title: ANED-Net: Adaptive Noise Estimation and Despeckling Network for SAR Image publication-title: IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. doi: 10.1109/JSTARS.2024.3355220 – volume: 15 start-page: 3 year: 2022 ident: ref_29 article-title: SAR Image Despeckling Using Continuous Attention Module publication-title: IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. doi: 10.1109/JSTARS.2021.3132027 – ident: ref_27 doi: 10.3390/rs10020196 – ident: ref_65 doi: 10.3390/rs12061006 – ident: ref_30 doi: 10.3390/rs11131532 – volume: 61 start-page: 5218416 year: 2023 ident: ref_43 article-title: Segmentation-Guided Semantic-Aware Self-Supervised Denoising for SAR Image publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2023.3323485 – ident: ref_50 doi: 10.1109/IGARSS52108.2023.10282914 – volume: 13 start-page: 600 year: 2004 ident: ref_63 article-title: Image quality assessment: From error visibility to structural similarity publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2003.819861 – volume: 15 start-page: 380 year: 1981 ident: ref_17 article-title: Refined filtering of image noise using local statistics publication-title: Comput. Graph. Image Process. doi: 10.1016/S0146-664X(81)80018-4 – volume: 69 start-page: 133 year: 1981 ident: ref_19 article-title: An adaptive filter for smoothing noisy radar images publication-title: Proc. IEEE doi: 10.1109/PROC.1981.11935 – ident: ref_28 doi: 10.3390/rs11242921 – ident: ref_61 – volume: 62 start-page: 5226813 year: 2024 ident: ref_42 article-title: Multilevel Denoising for High-Quality SAR Object Detection in Complex Scenes publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2024.3489212 – ident: ref_55 doi: 10.1109/CVPR52688.2022.00564 – ident: ref_35 doi: 10.1109/IGARSS46834.2022.9884596 – volume: 16 start-page: 6372 year: 2023 ident: ref_31 article-title: A Deep Neural Network Based on Prior-Driven and Structural Preserving for SAR Image Despeckling publication-title: IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. doi: 10.1109/JSTARS.2023.3292325 – ident: ref_64 doi: 10.1109/ICPR.2010.579 – volume: 24 start-page: 1763 year: 2017 ident: ref_26 article-title: SAR Image Despeckling Using a Convolutional Neural Network publication-title: IEEE Signal Process. Lett. doi: 10.1109/LSP.2017.2758203 – volume: 62 start-page: 5106315 year: 2024 ident: ref_51 article-title: Sentinel-1 Dual-Polarization SAR Images Despeckling Network Based on Unsupervised Learning publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 83 start-page: 58181 year: 2024 ident: ref_24 article-title: A comprehensive review of image denoising in deep learning publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-023-17468-2 – volume: 105 start-page: 1865 year: 2017 ident: ref_57 article-title: Remote Sensing Image Scene Classification: Benchmark and State of the Art publication-title: Proc. IEEE doi: 10.1109/JPROC.2017.2675998 – volume: 21 start-page: 4007905 year: 2024 ident: ref_3 article-title: DiffDet4SAR: Diffusion-Based Aircraft Target Detection Network for SAR Images publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2024.3386020 – ident: ref_12 doi: 10.3390/rs15235462 – ident: ref_25 doi: 10.1109/IGARSS.2017.8128234 – volume: 18 start-page: 2661 year: 2009 ident: ref_21 article-title: Iterative Weighted Maximum Likelihood Denoising with Probabilistic Patch-Based Weights publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2009.2029593 – volume: 28 start-page: 4633 year: 2021 ident: ref_15 article-title: A Review on SAR Image and its Despeckling publication-title: Arch. Comput. Methods Eng. doi: 10.1007/s11831-021-09548-z – ident: ref_20 – volume: 123 start-page: 106444 year: 2023 ident: ref_45 article-title: SAR ship localization method with denoising and feature refinement publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2023.106444 – ident: ref_59 – volume: 7 start-page: 165 year: 1985 ident: ref_18 article-title: Adaptive noise smoothing filter for images with signal-dependent noise publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.1985.4767641 – volume: 27 start-page: 63 year: 2023 ident: ref_2 article-title: Ship detection based on deep learning using SAR imagery: A systematic literature review publication-title: Soft Comput. doi: 10.1007/s00500-022-07522-w – ident: ref_40 doi: 10.1109/IRASET60544.2024.10549456 – volume: 34 start-page: 085403 year: 2023 ident: ref_48 article-title: Synthetic aperture radar images denoising based on multi-scale attention cascade convolutional neural network publication-title: Meas. Sci. Technol. doi: 10.1088/1361-6501/acd1a6 – ident: ref_14 doi: 10.3390/electronics14101950 – volume: 14 start-page: 37 year: 2021 ident: ref_23 article-title: A comprehensive review of SAR image filtering techniques: Systematic survey and future directions publication-title: Arab. J. Geosci. doi: 10.1007/s12517-020-06416-1 – volume: 63 start-page: 5625714 year: 2025 ident: ref_56 article-title: Cross-Layer Feature Pyramid Transformer for Small Object Detection in Aerial Images publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2025.3572706 – volume: 8 start-page: 17792 year: 2020 ident: ref_47 article-title: A Two-Component Deep Learning Network for SAR Image Denoising publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2965173 – ident: ref_39 doi: 10.1007/978-3-031-78354-8_29 – ident: ref_36 doi: 10.1109/ICTC55196.2022.9952991 – volume: 44 start-page: 7057 year: 2023 ident: ref_34 article-title: ViT-DexiNet: A Vision Transformer-Based Edge Detection Operator for Small Object Detection in SAR Images publication-title: Int. J. Remote Sens. doi: 10.1080/01431161.2023.2277167 – volume: 32 start-page: 021609 year: 2022 ident: ref_16 article-title: Review on nontraditional perspectives of synthetic aperture radar image despeckling publication-title: J. Electron. Imaging doi: 10.1117/1.JEI.32.2.021609 – volume: 83 start-page: 54615 year: 2024 ident: ref_9 article-title: Speckle noise reduction in SAR images using improved filtering and supervised classification publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-023-17648-0 – volume: 16 start-page: 2080 year: 2007 ident: ref_22 article-title: Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2007.901238 – volume: 62 start-page: 5206812 year: 2024 ident: ref_13 article-title: Robust Block Subspace Filtering for Efficient Removal of Radio Interference in Synthetic Aperture Radar Images publication-title: IEEE Trans. Geosci. Remote Sens. – ident: ref_8 doi: 10.3390/rs15020330 – volume: 284 start-page: 113369 year: 2023 ident: ref_5 article-title: Quantifying the sensitivity of L-Band SAR to a decade of vegetation structure changes in savannas publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2022.113369 – volume: 26 start-page: 620 year: 2022 ident: ref_62 article-title: SARBuD1.0: A SAR Building Dataset Based on GF-3 FSII Imageries for Built-up Area Extraction with Deep Learning Method publication-title: Natl. Remote Sens. Bull. doi: 10.11834/jrs.20220296 – volume: 61 start-page: 5216812 year: 2023 ident: ref_52 article-title: SAR Despeckling Using Multiobjective Neural Network Trained with Generic Statistical Samples publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2023.3314857 – volume: 36 start-page: 2290 year: 2023 ident: ref_54 article-title: HCformer: Hybrid CNN-Transformer for LDCT Image Denoising publication-title: J. Digit. Imaging doi: 10.1007/s10278-023-00842-9 – ident: ref_6 doi: 10.3390/rs15020308 – volume: 62 start-page: 5205515 year: 2024 ident: ref_53 article-title: LG-DBNet: Local and Global Dual-Branch Network for SAR Image Denoising publication-title: IEEE Trans. Geosci. Remote Sens. – ident: ref_41 doi: 10.3390/electronics12224595 – volume: 16 start-page: 1395 year: 2007 ident: ref_58 article-title: Pointwise Shape-Adaptive DCT for High-Quality Denoising and Deblocking of Grayscale and Color Images publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2007.891788 – volume: 62 start-page: 5211912 year: 2024 ident: ref_37 article-title: Trans-NLM Network for SAR Image Despeckling publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2024.3397325 – ident: ref_33 doi: 10.3390/rs15071860 – volume: 26 start-page: 3142 year: 2017 ident: ref_46 article-title: Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2017.2662206 – ident: ref_4 doi: 10.3390/s23146342 – ident: ref_32 doi: 10.1109/RADAR58436.2024.10993737 – volume: 14 start-page: 4321 year: 2021 ident: ref_49 article-title: SAR2SAR: A Semi-Supervised Despeckling Algorithm for SAR Images publication-title: IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. doi: 10.1109/JSTARS.2021.3071864
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SubjectTerms	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
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Title	DATNet: Dynamic Adaptive Transformer Network for SAR Image Denoising
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