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A Super-Resolution Reconstruction Network of Space Target Images Based on Dual Regression and Deformable Convolutional Attention Mechanism
Y. Shi, C. Jiang, C. H. Liu, W. H. Li and Z. Y. Wu
2023
发表期刊Electronics
卷号12期号:13页码:13
摘要High-quality space target images are important for space surveillance and space attack defense confrontation. To obtain space target images with higher resolution and sharpness, this paper proposes an image super-resolution reconstruction network based on dual regression and a deformable convolutional attention mechanism (DCAM). Firstly, the mapping space is constrained by dual regression; secondly, deformable convolution is used to expand the perceptual field and extract the high-frequency features of the image; finally, the convolutional attention mechanism is used to calculate the saliency of the channel domain and the spatial domain of the image to enhance the useful features and suppress the useless feature responses. The experimental results show that the method outperforms the comparison algorithm in both objective quality evaluation index and localization accuracy on the space target image dataset compared with the current mainstream image super-resolution algorithms.
DOI10.3390/electronics12132995
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收录类别sci
语种英语
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文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/67842
专题中国科学院长春光学精密机械与物理研究所
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GB/T 7714
Y. Shi, C. Jiang, C. H. Liu, W. H. Li and Z. Y. Wu. A Super-Resolution Reconstruction Network of Space Target Images Based on Dual Regression and Deformable Convolutional Attention Mechanism[J]. Electronics,2023,12(13):13.
APA Y. Shi, C. Jiang, C. H. Liu, W. H. Li and Z. Y. Wu.(2023).A Super-Resolution Reconstruction Network of Space Target Images Based on Dual Regression and Deformable Convolutional Attention Mechanism.Electronics,12(13),13.
MLA Y. Shi, C. Jiang, C. H. Liu, W. H. Li and Z. Y. Wu."A Super-Resolution Reconstruction Network of Space Target Images Based on Dual Regression and Deformable Convolutional Attention Mechanism".Electronics 12.13(2023):13.
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