ANALYSIS OF THE PRINCIPLES OF IMPROVING THE QUALITY OF IMAGES THROUGH THE PRISM OF BICUBIC INTERPOLATION AND CONVOLUTIONAL NEURAL NETWORKS

The article examines the achievements of modern methods of real-time image scaling. The purpose of this article is to analyze various methods and algorithms used for image scaling to improve the resolution and visual quality of low-resolution files, namely bicubic interpolation and convolutional neural network methods. The conclusions drawn from this analysis provide insight into the current state and future directions of real-time computer graphics.