摘要
多光谱融合是现代光谱分析技术的一个重要研究和发展方向,通过优化和整合不同类型的光谱,实现多光谱的信息互补和协同,结合化学计量学方法构建模型,可提高模型预测准确性和鲁棒性。本文系统介绍了多光谱融合策略和算法,包括经典的融合策略、基于多块算法的融合、基于多维算法的融合和基于深度学习的融合。分别对单光谱融合、两光谱融合、三光谱融合以及光谱与其他信息融合的应用研究进行了归纳和论述,在此基础上评述了光谱融合方法优缺点、局限性及基本选择原则。最后,探讨了多光谱融合分析技术所面临的挑战及后续发展方向。
Multispectral fusion is an important research and development direction in modern spectral analysis techniques.It realizes the information complementarity and synergy of multispectral data by optimizing and integrating different types of spectra.Combined with chemometric methods,it can improve the prediction accuracy and robustness of the models.This paper systematically introduces multispectral fusion strategies and algorithms,including classic fusion strategies,fusion based on multi-block algorithms,fusion based on multi-way algorithms,and fusion based on deep learning.The application research on single-spectral fusion,two-spectral fusion,three-spectral fusion,and the fusion of spectra with other information is respectively summarized and discussed.On this basis,the advantages and disadvantages,limitations,and basic selection principles of spectral fusion methods are reviewed.Finally,the challenges faced by multispectral fusion analysis techniques and the future prospects are discussed.
作者
杨健
刘宇
李敬岩
陈瀑
许育鹏
刘丹
褚小立
Jian Yang;Yu Liu;Jingyan Li;Pu Chen;Yupeng Xu;Dan Liu;Xiaoli Chu(Sinopec Research Institute of Petroleum Processing Co.,LTD.,Beijing 100083,China)
出处
《化学进展》
CSCD
北大核心
2024年第12期1874-1892,共19页
Progress in Chemistry
