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

doi:10.3390/rs14051243

CIOMP OpenIR

	Remote Sensing Image Denoising Based on Deep and Shallow Feature Fusion and Attention Mechanism
	L. T. Han; Y. C. Zhao; H. Y. Lv; Y. S. Zhang; H. L. Liu and G. L. Bi
	2022
发表期刊	Remote Sensing
卷号	14 期号:5 页码:23
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.
DOI	10.3390/rs14051243
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收录类别	sci ; ei
语种	英语
引用统计
文献类型	期刊论文
条目标识符	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.

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