Hyperspectral image classification using 3D-2D CNN with multi-scale information extraction and fusion module

Hang Gong; Tingkui Mu; Qiuxia Li; Feng Han; Abudusalamu Tuniyazi; Haoyang Li; Wenjing Wang; Zhiping He; Chunlai Li; Haishan Dai

doi:10.1117/12.2586803

15 January 2021 Hyperspectral image classification using 3D-2D CNN with multi-scale information extraction and fusion module

Hang Gong, Tingkui Mu, Qiuxia Li, Feng Han, Abudusalamu Tuniyazi, Haoyang Li, Wenjing Wang, Zhiping He, Chunlai Li, Haishan Dai

Author Affiliations +

Proceedings Volume 11761, Fourth International Conference on Photonics and Optical Engineering; 1176116 (2021) https://doi.org/10.1117/12.2586803
Event: Fourth International Conference on Photonics and Optical Engineering, 2020, Xi'an, China

Abstract

Classification is the focus and difficulty of hyperspectral imaging technology. Hyperspectral data have twodimensional spatial information and one-dimensional spectral information, which are presented as three-dimensional data blocks with large amount of information, meanwhile high-dimension, high nonlinearity and limited training samples bring great challenges. Deep learning can extract and analyze the features of target data step by step by building multi-layer deep nonlinear structure. The advanced feature, multi scale abstract information extracted by convolution neural network applied to image processing can improve the classification accuracy of complex hyperspectral data. We regard pixel level hyperspectral classification as semantic segmentation network, and creatively introduce squeeze-and-excitation network and pyramid pooling network into hyperspectral classification network and proposed a model based on the structure of 2D-3D hybrid convolution neural network, it can learn deeper spatial spectral features and fusion to improve the accuracy and speed of hyperspectral classification.

Citation Download Citation

Hang Gong, Tingkui Mu, Qiuxia Li, Feng Han, Abudusalamu Tuniyazi, Haoyang Li, Wenjing Wang, Zhiping He, Chunlai Li, and Haishan Dai "Hyperspectral image classification using 3D-2D CNN with multi-scale information extraction and fusion module", Proc. SPIE 11761, Fourth International Conference on Photonics and Optical Engineering, 1176116 (15 January 2021); https://doi.org/10.1117/12.2586803

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