A Method of Image Restoration for Distortion of Object in Water-Air Cross-Media
Uneven water-air media distribution or irregular liquid flow can cause changes in light propagation, leading to blurring and distortion of the extracted image, which presents a challenge for object recognition accuracy. To address these issues, this paper proposes a repair network to correct object...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | http://dx.doi.org/10.1155/2024/8442383 |
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| author | Yuhe Gao Jishen Jia Lei Cai Meng Zhou Haojie Chai Jinze Jia |
| author_facet | Yuhe Gao Jishen Jia Lei Cai Meng Zhou Haojie Chai Jinze Jia |
| author_sort | Yuhe Gao |
| collection | DOAJ |
| description | Uneven water-air media distribution or irregular liquid flow can cause changes in light propagation, leading to blurring and distortion of the extracted image, which presents a challenge for object recognition accuracy. To address these issues, this paper proposes a repair network to correct object image distortion in water-air cross-media. Firstly, convolutional combination performs feature extraction on water-air cross-media images, which retains the same features at the same scale and marks feature points with large differences. Then, an attention correction module for geometric lines is proposed to correct geometric lines in water-air cross-media images by comparing and sensing the marked feature points with large differences and utilizing the line similarity in positive and negative samples. Finally, the blurring artifact elimination module eliminates artifacts caused by image blurring and geometric line correction by using multiscale fusion of individual U-Net information streams. This completes the image restoration of object distortion under water-air cross-media. The proposed method is feasible and effective for restoring aberrated objects in water-air cross-media environments, with numerous experiments conducted on water-air cross-media image datasets. |
| format | Article |
| id | doaj-art-29b4494dcbb3468c91c3009fbe9e19ad |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-29b4494dcbb3468c91c3009fbe9e19ad2025-08-20T03:17:40ZengWileyInternational Journal of Distributed Sensor Networks1550-14772024-01-01202410.1155/2024/8442383A Method of Image Restoration for Distortion of Object in Water-Air Cross-MediaYuhe Gao0Jishen Jia1Lei Cai2Meng Zhou3Haojie Chai4Jinze Jia5School of Mathematical SciencesSchool of Mathematical SciencesSchool of Artificial IntelligenceSchool of Mathematical SciencesSchool of Artificial IntelligenceSchool of ManagementUneven water-air media distribution or irregular liquid flow can cause changes in light propagation, leading to blurring and distortion of the extracted image, which presents a challenge for object recognition accuracy. To address these issues, this paper proposes a repair network to correct object image distortion in water-air cross-media. Firstly, convolutional combination performs feature extraction on water-air cross-media images, which retains the same features at the same scale and marks feature points with large differences. Then, an attention correction module for geometric lines is proposed to correct geometric lines in water-air cross-media images by comparing and sensing the marked feature points with large differences and utilizing the line similarity in positive and negative samples. Finally, the blurring artifact elimination module eliminates artifacts caused by image blurring and geometric line correction by using multiscale fusion of individual U-Net information streams. This completes the image restoration of object distortion under water-air cross-media. The proposed method is feasible and effective for restoring aberrated objects in water-air cross-media environments, with numerous experiments conducted on water-air cross-media image datasets.http://dx.doi.org/10.1155/2024/8442383 |
| spellingShingle | Yuhe Gao Jishen Jia Lei Cai Meng Zhou Haojie Chai Jinze Jia A Method of Image Restoration for Distortion of Object in Water-Air Cross-Media International Journal of Distributed Sensor Networks |
| title | A Method of Image Restoration for Distortion of Object in Water-Air Cross-Media |
| title_full | A Method of Image Restoration for Distortion of Object in Water-Air Cross-Media |
| title_fullStr | A Method of Image Restoration for Distortion of Object in Water-Air Cross-Media |
| title_full_unstemmed | A Method of Image Restoration for Distortion of Object in Water-Air Cross-Media |
| title_short | A Method of Image Restoration for Distortion of Object in Water-Air Cross-Media |
| title_sort | method of image restoration for distortion of object in water air cross media |
| url | http://dx.doi.org/10.1155/2024/8442383 |
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