现代电子技术2025，Vol.48Issue(7)：1-10,10.DOI:10.16652/j.issn.1004-373x.2025.07.001
基于特征过滤法和Stacking集成学习的无人机影像作物精细分类
UAV image fine crop classification based on feature filtering method and Stacking ensemble learning
摘要
Abstract
The feature redundancy in multiple typical crop classifications at present leads to confusion and low classification accuracy of crops of the same family,so this paper proposes a crop fine classification method that combines the feature filtering method for feature screen and Stacking ensemble learning.A new type of vegetation index is constructed by combining sensitive bands,and the threshold value is segmented,so as to realize crop region extraction.The color and texture features of different crops are extracted,and then the feature coefficients of a single type of crop and the coefficients of feature differences among crops are calculated,so as to realize the classification feature filtering method preference for each typical crop.Finally,a Stacking ensemble learning crop classification model that integrates multiple machine learning algorithms is constructed.Among them,the random forest(RF),support vector machine(SVM)and K-nearest neighbor(K-NN)algorithms are selected for the base learner in the first layer,and the logistic regression model is selected for the meta-learner in the second layer,so that the various typical crops are classified finely.The experimental results show that the overall classification accuracy and Kappa coefficient of the proposed method for the seven typical crops are 85.2%and 83.34%,respectively,which are 2.18%and 3.68%higher than the classification results without feature selection.To sum up,the proposed method has high classification accuracy,and can be used as a new method for the fine classification of multiple typical crops.关键词
作物分类/特征选择/Stacking集成学习/植被指数/阈值分割/衍生特征Key words
crop classification/feature selection/Stacking ensemble learning/vegetation index/threshold segmentation/derivative feature分类
电子信息工程引用本文复制引用
刘朝辉,杨风暴,张琳..基于特征过滤法和Stacking集成学习的无人机影像作物精细分类[J].现代电子技术,2025,48(7):1-10,10.基金项目
国家自然科学基金面上项目(61972363) （61972363）
中央引导地方科技发展资金项目(YDZJSX2021C008) （YDZJSX2021C008）
