The application of probability neural network in remote sensing image processing based on k-means

In this paper, we design an approach which is a combination of k-means clustering and probability neural network method to classify the remote sensing image. The proposed method allows the implementation of Kaufman approach to get clustering centers, which are used as initial centers in k-means algorithm. Then the image is divided into k number of clusters by using the k-means algorithm. Finally, the pixels are divided into k classes according to probability neural network. The results indicate that the classified image is consistent with the original image and all kinds of characteristics are relatively well preserved.