2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDCIS-1.5
Paper Title FS-Net: Filter Selection Network for Hyperspectral Reconstruction
Authors Liutao Yang, Zhongnian Li, Zongxiang Pei, Daoqiang Zhang, Nanjing University of Aeronautics and Astronautics, China
SessionCIS-1: Computational Imaging Systems
LocationArea J
Session Time:Monday, 20 September, 15:30 - 17:00
Presentation Time:Monday, 20 September, 15:30 - 17:00
Presentation Poster
Topic Computational Imaging Systems: Spectral Sensing
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Optimizing spectral filters for hyperspectral reconstruction has received increasing attentions recently.However, current filter selection methods suffer from extremely high computational complexity due to exhaustive optimization.In this paper, in order to reduce the computational complexity, we propose a novel Filter Selection Network (FS-Net) to select filters and learn the reconstruction network simultaneously. Specifically, we propose an end-to-end method to embed filter selection in FS-Net by setting spectral response functions as the input layer. Furthermore, we propose a non-negative L1 sparse regularization (NN-L1) to select optical filters automatically by sparsifying the input layer. Besides, we develop a two-stage training strategy for adjusting the number of selected filters. Experiments on public datasets show that our proposed method can considerably improve the reconstruction quality.