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Restoration of Spatially Variant Blurred Images with Wide-Field Telescope Based on Deep Learning
Y. Tian, J. Wang, J. Liu and X. Guo
2023
发表期刊Sensors
ISSN14248220
卷号23期号:7
摘要The wide-field telescope is a research hotspot in the field of aerospace. Increasing the field of view of the telescope can expand the observation range and enhance the observation ability. However, a wide field will cause some spatially variant optical aberrations, which makes it difficult to obtain stellar information accurately from astronomical images. Therefore, we propose a network for restoring wide-field astronomical images by correcting optical aberrations, called ASANet. Based on the encoder–decoder structure, ASANet improves the original feature extraction module, adds skip connection, and adds a self-attention module. With these methods, we enhanced the capability to focus on the image globally and retain the shallow features in the original image to the maximum extent. At the same time, we created a new dataset of astronomical aberration images as the input of ASANet. Finally, we carried out some experiments to prove that the structure of ASANet is meaningful from two aspects of the image restoration effect and quality evaluation index. According to the experimental results, compared with other deblur networks, the PSNR and SSIM of ASANet are improved by about 0.5 and 0.02 db, respectively. © 2023 by the authors.
DOI10.3390/s23073745
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收录类别sci ; ei
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文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/67896
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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Y. Tian, J. Wang, J. Liu and X. Guo. Restoration of Spatially Variant Blurred Images with Wide-Field Telescope Based on Deep Learning[J]. Sensors,2023,23(7).
APA Y. Tian, J. Wang, J. Liu and X. Guo.(2023).Restoration of Spatially Variant Blurred Images with Wide-Field Telescope Based on Deep Learning.Sensors,23(7).
MLA Y. Tian, J. Wang, J. Liu and X. Guo."Restoration of Spatially Variant Blurred Images with Wide-Field Telescope Based on Deep Learning".Sensors 23.7(2023).
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