The Research on Image Classification of Remote Sensing Based on an Improved Neural Network

With higher spatial resolution, the image classification of remote sensing is always a hot research field. Besides spectral information, texture information from remote sensing image of higher spatial resolution has become an important data source to improve the classification accuracy. The image classification approach adopts an improved neural network, which contains two steps connected by the refusal principle. Two steps of input neurons are spectral information, using 3times3 window size, and texture information from gray co-occurrence matrix, which is selected by the genetic algorithms. The final result which is to overlay of above results get higher accuracy that the traditional method that ANN combine simply all of information from different source as input neurons.