Aerial Image Information Extraction Based on Non-negative Matrix Factorization

This study was on superiority of the non- negative matrix factorization（NMF） algorithm for application of information extracted with aerial images.First,NMF was used for aerial image information extraction,and then this data was compared with a principal component analysis（PCA） in which r（the number of rows or columns of basic matrix） and Eignum（the number of eigenvalues） were given different values.Experimental results showed that the run time of NMF with r = 20 or 50 was less than that of PCA with an Eignum = 20 or 50.Also,the recognition rate of NMF with r = 50 was higher than that of an Eignum = 50.The experiment showed that nonnegative matrix factorization had advantages of a short time period with a high recognition rate.