Remote sensing images have been a widely applications in Resource survey. In this paper, using K-means algorithm for hyperspectral remote sensing image classification. First introduced the technology of remote sensing images at home and abroad and the trend of the development ,and the the characteristics of the Hyperspectral remote sensing images. Then introduced the hyperspectral remote sensing images of several pre-processing method——calibrating the Hyperspectral remote sensing images.
In remote sensing image classification method,introduced a variety of hyperspectral remote sensing image classification method. The main algorithm can be divided into supervised classification and unsupervised classification algorithm. K-means algorithm is one commonly used in a non-supervised classification algorithm.
K-means classification algorithm in the first election with the smallest maximum-force category to choose the initial center, and then on the basis of minimum distance between the pixel points in all categories.
Final analysis of the different iterations of the final classification results.
The classification process of the experiment in the use of VC + + 2008 as a development platform, this platform greatly enhance the speed of classification.