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240313s2024 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2024.3374093
|2 doi
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|a eng
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| 100 |
1 |
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|a Zhao, Yin-Ping
|e verfasserin
|4 aut
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| 245 |
1 |
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|a RCUMP
|b Residual Completion Unrolling With Mixed Priors for Snapshot Compressive Imaging
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|c 2024
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Revised 26.03.2024
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a Deep unrolling-based snapshot compressive imaging (SCI) methods, which employ iterative formulas to construct interpretable iterative frameworks and embedded learnable modules, have achieved remarkable success in reconstructing 3-dimensional (3D) hyperspectral images (HSIs) from 2D measurement induced by coded aperture snapshot spectral imaging (CASSI). However, the existing deep unrolling-based methods are limited by the residuals associated with Taylor approximations and the poor representation ability of single hand-craft priors. To address these issues, we propose a novel HSI construction method named residual completion unrolling with mixed priors (RCUMP). RCUMP exploits a residual completion branch to solve the residual problem and incorporates mixed priors composed of a novel deep sparse prior and mask prior to enhance the representation ability. Our proposed CNN-based model can significantly reduce memory cost, which is an obvious improvement over previous CNN methods, and achieves better performance compared with the state-of-the-art transformer and RNN methods. In this work, our method is compared with the 9 most recent baselines on 10 scenes. The results show that our method consistently outperforms all the other methods while decreasing memory consumption by up to 80%
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|a Journal Article
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1 |
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|a Zhang, Jiancheng
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Chen, Yongyong
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Wang, Zhen
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Li, Xuelong
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 33(2024) vom: 26., Seite 2347-2360
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|x 1941-0042
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|g volume:33
|g year:2024
|g day:26
|g pages:2347-2360
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|u http://dx.doi.org/10.1109/TIP.2024.3374093
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