Color-Feature Extraction of Remote Sensing Image Based on Principal Components Analysis and K-means

This article propose a algorithm of PCA-K-means to extraction color feature of remote sensing image.The algorithm realizes the PCA algorithm and K-means algorithm which is suitable for mass data mining.The algorithm move the correlation of R, G and B.Using dynamic clustering method and classify on the basis of region by spatial consistency, the classification algorithm can describe the color feature of the remote sensing image.Experimental results that algorithm of PCA-K-mean has better performance in classification of the remote sensing image.