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HerosNet: Hyperspectral Explicable Reconstruction and Optimal Sampling Deep Network for Snapshot Compressive Imaging

arXiv 2112.06238 ↗First posted 12 Dec 2021cs.CV eess.IVcited by 26

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Abstract (arXiv)

Hyperspectral imaging is an essential imaging modality for a wide range of applications, especially in remote sensing, agriculture, and medicine. Inspired by existing hyperspectral cameras that are either slow, expensive, or bulky, reconstructing hyperspectral images (HSIs) from a low-budget snapshot measurement has drawn wide attention. By mapping a truncated numerical optimization algorithm into a network with a fixed number of phases, recent deep unfolding networks (DUNs) for spectral snapshot compressive sensing (SCI) have achieved remarkable success. However, DUNs are far from reaching the scope of industrial applications limited by the lack of cross-phase feature interaction and adaptive parameter adjustment. In this paper, we propose a novel Hyperspectral Explicable Reconstruction and Optimal Sampling deep Network for SCI, dubbed HerosNet, which includes several phases under the ISTA-unfolding framework. Each phase can flexibly simulate the sensing matrix and contextually adjust the step size in the gradient descent step, and hierarchically fuse and interact the hidden states of previous phases to effectively recover current HSI frames in the proximal mapping step. Simultaneously, a hardware-friendly optimal binary mask is learned end-to-end to further improve the reconstruction performance. Finally, our HerosNet is validated to outperform the state-of-the-art methods on both simulation and real datasets by large margins. The source code is available at https://github.com/jianzhangcs/HerosNet.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). Builds on 11 of its 56 references that are in the map. First posted on arXiv 12 Dec 2021.

Builds on

11 of 56 references.

References · 11

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2018Rank Minimization for Snapshot Compressive Imagingcited by 99
  3. 2020Plug-and-Play Algorithms for Large-scale Snapshot Compressive Imagingcited by 78
  4. 2021Deep Gaussian Scale Mixture Prior for Spectral Compressive Imagingcited by 58
  5. 2020GAP-net for Snapshot Compressive Imagingcited by 54
  6. 2021ISTA-Net++: Flexible Deep Unfolding Network for Compressive Sensingcited by 39
  7. 2021Memory-Augmented Deep Unfolding Network for Compressive Sensingcited by 38
  8. 2021COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensingcited by 32
  9. 2021Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imagingcited by 31
  10. 2014Image Compressive Sensing Recovery Using Adaptively Learned Sparsifying Basis via L0 Minimizationcited by 13
  11. 2020Hyperspectral Super-Resolution via Interpretable Block-Term Tensor Modelingcited by 10

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 12; 2024: 7; 2025: 2; 2026: 3.

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  1. 2023EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protectioncited by 109
  2. 2023Implicit Neural Representation for Cooperative Low-light Image Enhancementcited by 92
  3. 2022Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imagingcited by 66
  4. 2023Binarized Spectral Compressive Imagingcited by 23
  5. 2022Residual Degradation Learning Unfolding Framework with Mixing Priors across Spectral and Spatial for Compressive Spectral Imagingcited by 22
  6. 2023Pixel Adaptive Deep Unfolding Transformer for Hyperspectral Image Reconstructioncited by 20
  7. 2023DiffLLE: Diffusion-guided Domain Calibration for Unsupervised Low-light Image Enhancementcited by 8
  8. 2023Progressive Content-aware Coded Hyperspectral Compressive Imagingcited by 6
  9. 2024ResVR: Joint Rescaling and Viewport Rendering of Omnidirectional Imagescited by 6
  10. 2023Dispersed Structured Light for Hyperspectral 3D Imagingcited by 4
  11. 2024RealOSR: Latent Guidance Boosts Diffusion-based Real-world Omnidirectional Image Super-Resolutionscited by 3
  12. 2026TalkPhoto: A Versatile Training-Free Conversational Assistant for Intelligent Image Editingcited by 3
14 more
  1. 2023Unfolding Framework with Prior of Convolution-Transformer Mixture and Uncertainty Estimation for Video Snapshot Compressive Imagingcited by 2
  2. 2024Dual Hyperspectral Mamba for Efficient Spectral Compressive Imagingcited by 2
  3. 2024Exploiting Frequency Correlation for Hyperspectral Image Reconstructioncited by 2
  4. 2023MLP-AMDC: An MLP Architecture for Adaptive-Mask-based Dual-Camera snapshot hyperspectral imagingcited by 1
  5. 2024Untrained Neural Nets for Snapshot Compressive Imaging: Theory and Algorithmscited by 1
  6. 2024Inter and Intra Prior Learning-based Hyperspectral Image Reconstruction Using Snapshot SWIR Metasurfacecited by 1
  7. 2025LRDUN: A Low-Rank Deep Unfolding Network for Efficient Spectral Compressive Imagingcited by 1
  8. 2026Deep LoRA-Unfolding Networks for Image Restorationcited by 1
  9. 2023DMDC: Dynamic-mask-based dual camera design for snapshot Hyperspectral Imagingcited by 0
  10. 2023Computational Spectral Imaging with Unified Encoding Model: A Comparative Study and Beyondcited by 0
  11. 2023BSS-Bench: Towards Reproducible and Effective Band Selection Searchcited by 0
  12. 2024Self-Supervised One-Step Diffusion Refinement for Snapshot Compressive Imagingcited by 0
  13. 2025SlowFast-SCI: Slow-Fast Deep Unfolding Learning for Spectral Compressive Imagingcited by 0
  14. 2026Aperture-aware Dispersion 5-D Light-field Imaging Spectrometercited by 0