mlsanityData to 14 Oct 2026

DMDC: Dynamic-mask-based dual camera design for snapshot Hyperspectral Imaging

arXiv 2308.01541 ↗First posted 3 Aug 2023eess.IV cs.CVcited by 0

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Abstract (arXiv)

Deep learning methods are developing rapidly in coded aperture snapshot spectral imaging (CASSI). The number of parameters and FLOPs of existing state-of-the-art methods (SOTA) continues to increase, but the reconstruction accuracy improves slowly. Current methods still face two problems: 1) The performance of the spatial light modulator (SLM) is not fully developed due to the limitation of fixed Mask coding. 2) The single input limits the network performance. In this paper we present a dynamic-mask-based dual camera system, which consists of an RGB camera and a CASSI system running in parallel. First, the system learns the spatial feature distribution of the scene based on the RGB images, then instructs the SLM to encode each scene, and finally sends both RGB and CASSI images to the network for reconstruction. We further designed the DMDC-net, which consists of two separate networks, a small-scale CNN-based dynamic mask network for dynamic adjustment of the mask and a multimodal reconstruction network for reconstruction using RGB and CASSI measurements. Extensive experiments on multiple datasets show that our method achieves more than 9 dB improvement in PSNR over the SOTA. (https://github.com/caizeyu1992/DMDC)

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 41 references that are in the map. First posted on arXiv 3 Aug 2023.

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17 of 41 references.

References · 17

  1. 2016Plug-and-Play ADMM for Image Restoration: Fixed Point Convergence and Applicationscited by 246
  2. 2019Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernelscited by 112
  3. 2021Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstructioncited by 110
  4. 2018Rank Minimization for Snapshot Compressive Imagingcited by 99
  5. 2020Plug-and-Play Algorithms for Large-scale Snapshot Compressive Imagingcited by 78
  6. 2022MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstructioncited by 72
  7. 2022Coarse-to-Fine Sparse Transformer for Hyperspectral Image Reconstructioncited by 67
  8. 2022HDNet: High-resolution Dual-domain Learning for Spectral Compressive Imagingcited by 66
  9. 2022Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imagingcited by 66
  10. 2021Deep Gaussian Scale Mixture Prior for Spectral Compressive Imagingcited by 58
  11. 2020GAP-net for Snapshot Compressive Imagingcited by 54
  12. 2021Plug-and-Play Algorithms for Video Snapshot Compressive Imagingcited by 42
5 more
  1. 2021Self-supervised Neural Networks for Spectral Snapshot Compressive Imagingcited by 35
  2. 2021HerosNet: Hyperspectral Explicable Reconstruction and Optimal Sampling Deep Network for Snapshot Compressive Imagingcited by 26
  3. 2022Residual Degradation Learning Unfolding Framework with Mixing Priors across Spectral and Spatial for Compressive Spectral Imagingcited by 22
  4. 2021Dual camera snapshot hyperspectral imaging system via physics informed learningcited by 3
  5. 2023SST-ReversibleNet: Reversible-prior-based Spectral-Spatial Transformer for Efficient Hyperspectral Image Reconstructioncited by 2

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