Image Upscaling Using AI

Abstract

Through creating an AI-driven picture upscaling solution using diffusion models, the study tackles the increasing need for improved visual material. Using a VRAM-efficient tile-based processing method, the system improves low-resolution pictures, allowing for super-resolution on regular GPU hardware.To overcome memory limitations that might occur while processing huge photos, the suggested approach uses Stable Diffusion ×4 upscaling technology in conjunction with sophisticated tiling methods. By reducing pictures to smaller tiles and using diffusion-based enhancement approaches, the method significantly increases detail while keeping computation efficient.The main characteristics of the system are its ability to use advanced diffusion models to drive upscaling, its compatibility with common GPU setups, its tile-based processing for optimizing VRAM, and its increased accessibility to low-hardware super-resolution technologies.Prototype successfully improves picture quality, lowering the barrier to entry for sophisticated AI upscaling methods that need expensive HPC infrastructure.