FRANet: A Feature Refinement Attention Network for SAR Image Denoising

Since synthetic aperture radar (SAR) images have complex noise and have no clean reference images, SAR image denoising is very challenging. With the development of deep learning, several denoising algorithms based on deep learning are proposed to achieve a better SAR image denoising effect. However,...

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Vydané v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 18; s. 12343 - 12363
Hlavní autori:	Liu, Shuaiqi, Lei, Yu, Hu, Qi, Liu, Ming, Li, Bing, Hu, Weiming, Zhang, Yu-Dong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Attention encoder–decoder network Coders Convolutional neural networks Deep learning Feature extraction feature refinement image denoising Information retrieval Machine learning Noise Noise measurement Noise reduction Radar imaging Radar polarimetry Receptive field Run time (computers) SAR (radar) Speckle Synthetic aperture radar synthetic aperture radar (SAR) Training Transforms
ISSN:	1939-1404, 2151-1535
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