A lightweight hyperspectral image classification framework based on spectral domain discretization

Chengcheng Zhong; Kai Zhang; Zitong Zhang; Chunlei Zhang

doi:10.1117/12.2667232

22 February 2023 A lightweight hyperspectral image classification framework based on spectral domain discretization

Chengcheng Zhong, Kai Zhang, Zitong Zhang, Chunlei Zhang

Proceedings Volume 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022); 1258716 (2023) https://doi.org/10.1117/12.2667232
Event: Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 2022, Shanghai, China

Abstract

In this paper, we propose a lightweight machine learning (ML) framework based on unsupervised spectral domain discretization for hyperspectral image (HSI) classification. Firstly, the high-dimensional HSI data is mapped into a discretized image by unsupervised learning method, and then the histogram statistics of discrete features are performed to align feature vectors. Finally, supervised ML method is used for classification, thus achieving a lightweight ML method of high-dimensional HSIs. Practical applications and comparative studies on three publicly available HSI datasets show that the framework approaches and surpasses deep learning models in classification accuracy while significantly compressing computational time consumption. The performance of six unsupervised clustering methods in HSI spectral domain discretization is compared in the study. Among them, K-means and GMM are superior in terms of classification accuracy. And SOM provides high classification accuracy while its discretization results are better interpretable due to better maintenance of topology during discretization.

Citation Download Citation

Chengcheng Zhong, Kai Zhang, Zitong Zhang, and Chunlei Zhang "A lightweight hyperspectral image classification framework based on spectral domain discretization", Proc. SPIE 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 1258716 (22 February 2023); https://doi.org/10.1117/12.2667232

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KEYWORDS

Deep learning

Machine learning

Feature extraction

Terrain classification

Hyperspectral imaging

Image classification

Data modeling

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