Obtaining Super-Resolution Satellites Images Based on Enhancement Deep Convolutional Neural Network

Super-resolution reconstruction refers to the technique of reconstructing a high-resolution image from a single or a series of low-resolution images by digital image processing. This technology can not only increase the high-frequency information of the image, but also eliminate the low-resolution. Deep Learning has made breakthroughs in modern digital image processing. Compared to traditional algorithms, deep convolutional neural networks (DCNN) achieve superior performance on a series of challenging image-processing problems such as image classification and target detection. Enhancement Deep convolutional neural networks (EDCNN) learn through a large number of training samples, obtain relevant information within the image, and then use the information to achieve specific functions. EDCNN also has an excellent performance with remote sensing data. Performance evaluation was made with bicubic and other deep learning methods, EDCNN outperformed other deep learning algorithms.