Improved algorithm for hyperspectral data dimension determination

International Symposium on Earth Observation for One Belt and One Road

地球科学;政治学;社会学;经济学

Chen, Jie^1,2 ; Du, Lei^1 ; Li, Jing^2 ; Han, Yachao^1 ; Gao, Zihong^1

China Aero Geophysical Survey and Remote Sensing Centre for Land and Resources, Beijing

100083, China^1

Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing

100101, China^2

关键词: De correlations;    Hyperspectral Data;    Hyperspectral image datas;    Hyperspectral signals;    Noise covariance matrix;    Noise whitening;    Signal correlation;    Spectral dimensions;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/57/1/012044/pdf
DOI  :  10.1088/1755-1315/57/1/012044

来源: IOP

【 摘 要 】

The correlation between adjacent bands of hyperspectral image data is relatively strong. However, signal coexists with noise and the HySime (hyperspectral signal identification by minimum error) algorithm which is based on the principle of least squares is designed to calculate the estimated noise value and the estimated signal correlation matrix value. The algorithm is effective with accurate noise value but ineffective with estimated noise value obtained from spectral dimension reduction and de-correlation process. This paper proposes an improved HySime algorithm based on noise whitening process. It carries out the noise whitening, instead of removing noise pixel by pixel, process on the original data first, obtains the noise covariance matrix estimated value accurately, and uses the HySime algorithm to calculate the signal correlation matrix value in order to improve the precision of results. With simulated as well as real data experiments in this paper, results show that: firstly, the improved HySime algorithm are more accurate and stable than the original HySime algorithm; secondly, the improved HySime algorithm results have better consistency under the different conditions compared with the classic noise subspace projection algorithm (NSP); finally, the improved HySime algorithm improves the adaptability of non-white image noise with noise whitening process.