摘要
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 E<sub>ignum</sub>（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 E<sub>ignum</sub> = 20 or 50.Also,the recognition rate of NMF with r = 50 was higher than that of an E<sub>ignum</sub> = 50.The experiment showed that nonnegative matrix factorization had advantages of a short time period with a high recognition rate.
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 E<sub>ignum</sub>（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 E<sub>ignum</sub> = 20 or 50.Also,the recognition rate of NMF with r = 50 was higher than that of an E<sub>ignum</sub> = 50.The experiment showed that nonnegative matrix factorization had advantages of a short time period with a high recognition rate.
