MAUN: Memory-Augmented Deep Unfolding Network for Hyperspectral Image Reconstruction
文献类型：期刊论文
| 作者 | Qian Hu; Jiayi Ma; Yuan Gao ; Junjun Jiang; Yixuan Yuan
|
| 刊名 | IEEE/CAA Journal of Automatica Sinica
 |
| 出版日期 | 2024 |
| 卷号 | 11期号:5页码:1139-1150 |
| 关键词 | Compressive imaging deep unfolding network hyperspectral image |
| ISSN号 | 2329-9266 |
| DOI | 10.1109/JAS.2024.124362 |
| 英文摘要 | Spectral compressive imaging has emerged as a powerful technique to collect the 3D spectral information as 2D measurements. The algorithm for restoring the original 3D hyperspectral images HSIs from compressive measurements is pivotal in the imaging process. Early approaches painstakingly designed networks to directly map compressive measurements to HSIs, resulting in the lack of interpretability without exploiting the imaging priors. While some recent works have introduced the deep unfolding framework for explainable reconstruction, the performance of these methods is still limited by the weak information transmission between iterative stages. In this paper, we propose a Memory-Augmented deep Unfolding Network, termed MAUN, for explainable and accurate HSI reconstruction. Specifically, MAUN implements a novel CNN scheme to facilitate a better extrapolation step of the fast iterative shrinkage-thresholding algorithm, introducing an extra momentum incorporation step for each iteration to alleviate the information loss. Moreover, to exploit the high correlation of intermediate images from neighboring iterations, we customize a cross-stage transformer CSFormer as the deep denoiser to simultaneously capture self-similarity from both in-stage and cross-stage features, which is the first attempt to model the long-distance dependencies between iteration stages. Extensive experiments demonstrate that the proposed MAUN is superior to other state-of-the-art methods both visually and metrically. Our code is publicly available at https://github.com/HuQ1an/MAUN . |
| 源URL | [http://ir.ia.ac.cn/handle/173211/55704]  |
| 专题 | 自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica |
| 推荐引用方式 GB/T 7714 | Qian Hu,Jiayi Ma,Yuan Gao,et al. MAUN: Memory-Augmented Deep Unfolding Network for Hyperspectral Image Reconstruction[J]. IEEE/CAA Journal of Automatica Sinica,2024,11(5):1139-1150. |
| APA | Qian Hu,Jiayi Ma,Yuan Gao,Junjun Jiang,&Yixuan Yuan.(2024).MAUN: Memory-Augmented Deep Unfolding Network for Hyperspectral Image Reconstruction.IEEE/CAA Journal of Automatica Sinica,11(5),1139-1150. |
| MLA | Qian Hu,et al."MAUN: Memory-Augmented Deep Unfolding Network for Hyperspectral Image Reconstruction".IEEE/CAA Journal of Automatica Sinica 11.5(2024):1139-1150. |
入库方式： OAI收割
来源：自动化研究所
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