mlsanityData to 7 Oct 2026

Inter and Intra Prior Learning-based Hyperspectral Image Reconstruction Using Snapshot SWIR Metasurface

arXiv 2407.07503 ↗First posted 10 Jul 2024cs.CV cs.IRcited by 1

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Abstract (arXiv)

Shortwave-infrared(SWIR) spectral information, ranging from 1 μm to 2.5μm, overcomes the limitations of traditional color cameras in acquiring scene information. However, conventional SWIR hyperspectral imaging systems face challenges due to their bulky setups and low acquisition speeds. This work introduces a snapshot SWIR hyperspectral imaging system based on a metasurface filter and a corresponding filter selection method to achieve the lowest correlation coefficient among these filters. This system offers the advantages of compact size and snapshot imaging. We propose a novel inter and intra prior learning unfolding framework to achieve high-quality SWIR hyperspectral image reconstruction, which bridges the gap between prior learning and cross-stage information interaction. Additionally, We design an adaptive feature transfer mechanism to adaptively transfer the contextual correlation of multi-scale encoder features to prevent detailed information loss in the decoder. Experiment results demonstrate that our method can reconstruct hyperspectral images with high speed and superior performance over existing methods.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 20 of its 62 references that are in the map. First posted on arXiv 10 Jul 2024.

Builds on

20 of 62 references.

References · 20

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2017Squeeze-and-Excitation Networkscited by 4,763
  3. 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,341
  4. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,618
  5. 2021Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstructioncited by 110
  6. 2018Rank Minimization for Snapshot Compressive Imagingcited by 99
  7. 2022Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognitioncited by 81
  8. 2020Plug-and-Play Algorithms for Large-scale Snapshot Compressive Imagingcited by 78
  9. 2022Coarse-to-Fine Sparse Transformer for Hyperspectral Image Reconstructioncited by 67
  10. 2022HDNet: High-resolution Dual-domain Learning for Spectral Compressive Imagingcited by 66
  11. 2022Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imagingcited by 66
  12. 2021Deep Gaussian Scale Mixture Prior for Spectral Compressive Imagingcited by 58
8 more
  1. 2020GAP-net for Snapshot Compressive Imagingcited by 54
  2. 2020Hierarchical Regression Network for Spectral Reconstruction from RGB Imagescited by 29
  3. 2021HerosNet: Hyperspectral Explicable Reconstruction and Optimal Sampling Deep Network for Snapshot Compressive Imagingcited by 26
  4. 2022Residual Degradation Learning Unfolding Framework with Mixing Priors across Spectral and Spatial for Compressive Spectral Imagingcited by 22
  5. 2015Compressive Hyperspectral Imaging with Side Informationcited by 19
  6. 2023Optimization-Inspired Cross-Attention Transformer for Compressive Sensingcited by 12
  7. 2018An efficient CNN for spectral reconstruction from RGB imagescited by 5
  8. 2020Dynamic brain spectrum acquired by a real-time ultra-spectral imaging chip with reconfigurable metasurfacescited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Broadband Hyperspectral 3D Imaging using Dispersed Structured Lightcited by 0