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Remote Sensing Image Denoising Based on Deep and Shallow Feature Fusion and Attention Mechanism

文献类型：期刊论文

作者L. T. Han; Y. C. Zhao; H. Y. Lv; Y. S. Zhang; H. L. Liu and G. L. Bi
刊名Remote Sensing
出版日期2022
卷号14期号:5页码:23
DOI10.3390/rs14051243
英文摘要Optical remote sensing images are widely used in the fields of feature recognition, scene semantic segmentation, and others. However, the quality of remote sensing images is degraded due to the influence of various noises, which seriously affects the practical use of remote sensing images. As remote sensing images have more complex texture features than ordinary images, this will lead to the previous denoising algorithm failing to achieve the desired result. Therefore, we propose a novel remote sensing image denoising network (RSIDNet) based on a deep learning approach, which mainly consists of a multi-scale feature extraction module (MFE), multiple local skip-connected enhanced attention blocks (ECA), a global feature fusion block (GFF), and a noisy image reconstruction block (NR). The combination of these modules greatly improves the model's use of the extracted features and increases the model's denoising capability. Extensive experiments on synthetic Gaussian noise datasets and real noise datasets have shown that RSIDNet achieves satisfactory results. RSIDNet can improve the loss of detail information in denoised images in traditional denoising methods, retaining more of the higher-frequency components, which can have performance improvements for subsequent image processing.
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语种英语
源URL[http://ir.ciomp.ac.cn/handle/181722/67033]  
专题中国科学院长春光学精密机械与物理研究所
推荐引用方式
GB/T 7714		 L. T. Han,Y. C. Zhao,H. Y. Lv,et al. Remote Sensing Image Denoising Based on Deep and Shallow Feature Fusion and Attention Mechanism[J]. Remote Sensing,2022,14(5):23.
APA L. T. Han,Y. C. Zhao,H. Y. Lv,Y. S. Zhang,&H. L. Liu and G. L. Bi.(2022).Remote Sensing Image Denoising Based on Deep and Shallow Feature Fusion and Attention Mechanism.Remote Sensing,14(5),23.
MLA L. T. Han,et al."Remote Sensing Image Denoising Based on Deep and Shallow Feature Fusion and Attention Mechanism".Remote Sensing 14.5(2022):23.

入库方式： OAI收割

来源：长春光学精密机械与物理研究所

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