Final Year Project - Enhancing Video Quality through AI-Powered Noise Removal Techniques

This project aimed to improve video quality by developing and comparing AI-based noise reduction techniques. We explored deep learning models like DnCNN, CLSTM and U-Net Autoencoder to efficiently eliminate noise while preserving image details. Through rigorous testing and evaluation using metrics such as PSNR and SSIM, we identified the most suitable model for different noise scenarios. Our findings contribute to advancing video processing and computer vision applications.