Method of Increasing the Resolution of the Images Based on Artificial Neural Networks

Abstract

This paper presents a new method for increasing the resolution of the image - based on the artificial neural networks. The advantage of the developed ANN's method based on models of geometric transformation is to achieve a high level of generalization in a limited sample of training data. A series of model experiments to establish optimal parameters for image preprocessing and ANN training are made. Experiment on the decomposition of the image to frames for to form learning sample showed that the ability to generalize significantly decreases with increasing block size, which affects the quality of the synthesized image. Changing the degree of nonlinearity of synapses in the graphical user interface func*net Express, which was used for training and testing of the method suggests that the increase of this index does not significantly affect the perception of the image. The theoretical conclusions obtained by visual analysis of the synthesized images are complemented by the result ofevaluation metrics MSE, PSNR, UIQ and SSIM. Comparative analysis of the images enlarged 4 times, obtained by our method and two existing, shows best scores on all four metrics, suggesting the possibility of practical application of the method in a particular application area