Image Compression Using Neural Networks: A Comprehensive Study of Efficiency and Quality

Abstract

Image compression is a critical component in modern digital communication and storage systems, with applications rangingfrom social media platforms to medical imaging. This research paper presents a novel approach to image compression using deep neural networks, aiming to achieve higher compression ratios while maintaining image quality. We propose a convolution neural network(CNN) architecture that learns to compress and decompress images effectively.