Cloud Removal from Satellite Images Using Auto Associative Neural Network and Stationary Wevlet Transform

In this paper an image fusion technique is developed to remove clouds from satellite images. The proposed method involves an auto associative neural network based PCAT (principal component transform) and SWT (stationary wavelet transform) to remove clouds recursively which integrates complementary information to form a composite image from multitemporal images. Some evaluation measures are suggested and applied to compare our method with those of covariance based PCAT fusion method and WT-based one. The PSNR and the correlation coefficient value indicate that the performance of the proposed method is better than others. It also enhances the visual effect.