现代电子技术2011，Vol.34Issue(13)：74-77,80,5.
一种改进的局部保持投影高光谱特征提取算法
An Improved Algorithm for Hyperspectral Data Feature Extraction in Locality Preserving Projections
屈晓刚 1何明一 1梅少辉1
作者信息
- 1. 西北工业大学陕西省信息获取与处理重点实验室，陕西西安 710129
- 折叠
摘要
Abstract
Since locality preserving projections (LPP) only preserves the local structure and cannot guarantee the extracted features helpful for classification, a feature extraction algorithm of semi-supervised preserving projections (SPP) is proposed. The proposed method can use the classification information carried by the labeled samples to restrain the unlabeled samples, so as to improve the divisibility of samples. Moreover, the problem of singular matrix is avoided by adding a regularization term to its objective function. Experiments on hyperspectral data demonstrate that the classification accuracy of SPP is significantly higher than that of LPP.关键词
局部保持投影；特征提取；半监督；高光谱Key words
locality preserving projection/ feature extraction/ semi-supervised learning/ hyperspectral data分类
信息技术与安全科学引用本文复制引用
屈晓刚,何明一,梅少辉..一种改进的局部保持投影高光谱特征提取算法[J].现代电子技术,2011,34(13):74-77,80,5.
