Hyperspectral Image Classification Using Wavelet Packet Analysis and Gray Prediction Model

摘要：

The main focus of hyperspectral image classification is the ability to extract information from a pixels hyperspectral curve. In this paper, we propose a new classification method based on wavelet packet analysis and gray prediction model of hyperspectral reflectance curves. The wavelet packet analysis is used for feature extraction, while the gray prediction model is applied for dimensionality reduction. The efficiency of the proposed method will be estimated by the multivariate statistical analysis (i.e. Mahalanobis distance and quantile). Experimental results indicate that our algorithm has a relatively high efficiency, and classification accuracy of 99.3%.

关键词： hyperspectral image wavelet packet analysis gray prediction model Mahalanobis distance quantile

作者: Jihao Yin Chao Gao Yifei Wang Yisong Wang

作者单位: School of Astronautics, Beijing University of Aeronautics and Astronautics Beijing, China

会议类型: 国际会议

会议名称: 2010 International Conference on Image Analysis and Signal Processing(2010 图像分析与信号处理国际会议 IASP 10)

会议地点: 厦门

会议语种:英文

页码: 322-326

在线出版日期: 2010-04-12（万方平台首次上网日期，不代表论文的发表时间）