红外与毫米波学报2023，Vol.42Issue(6)：825-833,9.DOI:10.11972/j.issn.1001-9014.2023.06.016
基于深度学习的高光谱影像分类方法研究
Research on hyperspectral image classification method based on deep learning
摘要
Abstract
Targeting the issue of insufficient accuracy of hyperspectral image classification methods,a hyperspectral im-age classification method based on Spatial-spatial transformer(SST)network is proposed.Firstly,the hyperspectral im-ages are preprocessed into one-dimensional feature vectors.Then,the SST hyperspectral image classification network with spectral-spatial attention module and pooled residual module is designed.The overall classification accuracy of the proposed classification method on Indian Pines dataset and Pavia University dataset is 98.67%and 99.87%,respective-ly,which indicates that this method has high classification accuracy and provides a new scheme for hyperspectral image classification and application.关键词
深度学习/高光谱影像/分类/遥感图像Key words
deep learning/hyperspectral image/classification/satellite imagery分类
信息技术与安全科学引用本文复制引用
张彬,刘亮,李晓杰,周伟..基于深度学习的高光谱影像分类方法研究[J].红外与毫米波学报,2023,42(6):825-833,9.基金项目
国家自然科学基金(62005318) Supported by the National Natural Science Foundation of China(62005318) （62005318）
