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 IDARS-9.6
Paper Title HYPERSPECTRAL CLASSIFICATION USING COOPERATIVE SPATIAL-SPECTRAL ATTENTION NETWORK WITH TENSOR LOW-RANK RECONSTRUCTION
Authors Sen Li, Xiaoyan Luo, Qixiong Wang, Lei Li, Weifa Shen, Jihao Yin, Beihang University, China
SessionARS-9: Interpretation, Understanding, Retrieval
LocationArea I
Session Time:Tuesday, 21 September, 13:30 - 15:00
Presentation Time:Tuesday, 21 September, 13:30 - 15:00
Presentation Poster
Topic Image and Video Analysis, Synthesis, and Retrieval: Image & Video Interpretation and Understanding
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Spatial and spectral attention networks have been both well introduced to Hyperspectral image (HSI) classification. However, in previous works, they are seldom considered jointly. To obtain a 3D spatial-spectral attention map, which is beneficial for extracting discriminative spatial-spectral features, we propose a novel cooperative spatial-spectral attention network with tensor low-rank reconstruction. Firstly, a tensor low-rank reconstruction (TLRR) block is designed to learn a spatial-spectral attention map tensor, which adaptively emphasizes the attention features of the salient spatial positions and informative spectral bands simultaneously. Secondly, these attention features are merged into simple convolutional features which are more discriminative for classification. Finally, the experimental results demonstrate that our proposed method outperforms some state-of-the-art methods on two typical HSI datasets.