MAUN: Memory-Augmented Deep Unfolding Network for Hyperspectral Image Reconstruction

doi:10.1109/JAS.2024.124362

CASIA OpenIR > 学术期刊 > IEEE/CAA Journal of Automatica Sinica

	MAUN: Memory-Augmented Deep Unfolding Network for Hyperspectral Image Reconstruction
	Qian Hu; Jiayi Ma; Yuan Gao; Junjun Jiang; Yixuan Yuan
发表期刊	IEEE/CAA Journal of Automatica Sinica
ISSN	2329-9266
	2024
卷号	11 期号:5 页码:1139-1150
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 .
关键词	Compressive imaging deep unfolding network hyperspectral image
DOI	10.1109/JAS.2024.124362
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/55704
专题	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.

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