Satellite Image Restoration via an Adaptive QWNNM Model
Due to channel noise and random atmospheric turbulence, retrieved satellite images are always distorted and degraded and so require further restoration before use in various applications. The latest quaternion-based weighted nuclear norm minimization (QWNNM) model, which utilizes the idea of low-ran...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/16/22/4152 |
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| author | Xudong Xu Zhihua Zhang M. James C. Crabbe |
| author_facet | Xudong Xu Zhihua Zhang M. James C. Crabbe |
| author_sort | Xudong Xu |
| collection | DOAJ |
| description | Due to channel noise and random atmospheric turbulence, retrieved satellite images are always distorted and degraded and so require further restoration before use in various applications. The latest quaternion-based weighted nuclear norm minimization (QWNNM) model, which utilizes the idea of low-rank matrix approximation and the quaternion representation of multi-channel satellite images, can achieve image restoration and enhancement. However, the QWNNM model ignores the impact of noise on similarity measurement, lacks the utilization of residual image information, and fixes the number of iterations. In order to address these drawbacks, we propose three adaptive strategies: adaptive noise-resilient block matching, adaptive feedback of residual image, and adaptive iteration stopping criterion in a new adaptive QWNNM model. Both simulation experiments with known noise/blurring and real environment experiments with unknown noise/blurring demonstrated that the effectiveness of adaptive QWNNM models outperformed the original QWNNM model and other state-of-the-art satellite image restoration models in very different technique approaches. |
| format | Article |
| id | doaj-art-669c9b7eb0b94eb7b5bdef9cbb9f00a3 |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-669c9b7eb0b94eb7b5bdef9cbb9f00a32025-08-20T02:27:38ZengMDPI AGRemote Sensing2072-42922024-11-011622415210.3390/rs16224152Satellite Image Restoration via an Adaptive QWNNM ModelXudong Xu0Zhihua Zhang1M. James C. Crabbe2Interdisciplinary Data Mining Group, School of Mathematics, Shandong University, Jinan 250100, ChinaInterdisciplinary Data Mining Group, School of Mathematics, Shandong University, Jinan 250100, ChinaWolfson College, Oxford University, Oxford OX2 6UD, UKDue to channel noise and random atmospheric turbulence, retrieved satellite images are always distorted and degraded and so require further restoration before use in various applications. The latest quaternion-based weighted nuclear norm minimization (QWNNM) model, which utilizes the idea of low-rank matrix approximation and the quaternion representation of multi-channel satellite images, can achieve image restoration and enhancement. However, the QWNNM model ignores the impact of noise on similarity measurement, lacks the utilization of residual image information, and fixes the number of iterations. In order to address these drawbacks, we propose three adaptive strategies: adaptive noise-resilient block matching, adaptive feedback of residual image, and adaptive iteration stopping criterion in a new adaptive QWNNM model. Both simulation experiments with known noise/blurring and real environment experiments with unknown noise/blurring demonstrated that the effectiveness of adaptive QWNNM models outperformed the original QWNNM model and other state-of-the-art satellite image restoration models in very different technique approaches.https://www.mdpi.com/2072-4292/16/22/4152satellite imagesimage restoration and enhancementadaptive noise-resilient block matchingadaptive feedback of residual imagesadaptive iteration stopping criterion |
| spellingShingle | Xudong Xu Zhihua Zhang M. James C. Crabbe Satellite Image Restoration via an Adaptive QWNNM Model Remote Sensing satellite images image restoration and enhancement adaptive noise-resilient block matching adaptive feedback of residual images adaptive iteration stopping criterion |
| title | Satellite Image Restoration via an Adaptive QWNNM Model |
| title_full | Satellite Image Restoration via an Adaptive QWNNM Model |
| title_fullStr | Satellite Image Restoration via an Adaptive QWNNM Model |
| title_full_unstemmed | Satellite Image Restoration via an Adaptive QWNNM Model |
| title_short | Satellite Image Restoration via an Adaptive QWNNM Model |
| title_sort | satellite image restoration via an adaptive qwnnm model |
| topic | satellite images image restoration and enhancement adaptive noise-resilient block matching adaptive feedback of residual images adaptive iteration stopping criterion |
| url | https://www.mdpi.com/2072-4292/16/22/4152 |
| work_keys_str_mv | AT xudongxu satelliteimagerestorationviaanadaptiveqwnnmmodel AT zhihuazhang satelliteimagerestorationviaanadaptiveqwnnmmodel AT mjamesccrabbe satelliteimagerestorationviaanadaptiveqwnnmmodel |