A Novel Neural Network Based Meteorological Image Prediction from a Given Sequence of Images

A novel neural network method to predict the spectral signature in the predicted meteorological image is presented here. Back propagation algorithm has been used in this work. Based on computation cost, three different dimensional feature vectors are provided from two consecutive images as input to neural net for training and testing. Various kinds of testing are made depending upon position of predicted images and input images. We divide the intensity levels of each image by four clusters using K-means clustering method and we build different neural nets for each corresponding cluster. Mean Square Error is used to evaluate the performance of the net and PSNR is used to judge the accuracy of predicted image. Results are encouraging.