Improve the Quality of Images UAVs and Small Satellites using Super-Resolution Techniques

Theoretical and practical limits effect on resolution imaging systems and the effective ways to overcome these limits, super-resolution methods that have been developed at recent years. The main purpose of this paper, in addition magnified digital images, restore missing high frequency detail. In this paper, a method called single-frame resolution using a convolution neural network (CNN) based on optimization genetic algorithms (GA) provided better results to improve images than traditional super-resolution methods. Results show that our method achieved an improved performance compared to other super-resolution based methods, and the proposed method increases the quality of the image based on PSNR metric. The amount of this improvement is about 10% compared to super-resolution based approaches.