This project focuses on image enhancement using Convolutional Neural Networks (CNNs) to improve the quality and clarity of noisy images. Image enhancement techniques are applied to reduce noise, sharpen details, and improve brightness, resulting in cleaner and more understandable outputs. The system utilizes CNN architecture along with the naïve gradient descent learning algorithm to process digitized images and generate enhanced visual results. By leveraging deep learning techniques, the project demonstrates the effectiveness of CNNs in handling image restoration tasks and producing robust outputs even in noisy conditions. The system highlights the growing importance of machine learning and image processing in improving digital image quality for practical applications.