Image Resolution

Image resolution enhancement focuses on improving the detail and clarity of images, primarily through computational methods rather than hardware upgrades. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs), generative adversarial networks (GANs), and diffusion models to achieve super-resolution, often applied to specific image types like satellite imagery, medical scans, and microscopy images. These advancements are significant for various fields, improving diagnostic accuracy in medicine, enhancing the quality of remote sensing data, and enabling more detailed analysis in scientific imaging. The development of lightweight and efficient models is a key focus to broaden the applicability of these techniques.