Image Enhancement of Low Light Image using Deep Learning

Abstract

Image enhancement of low light images is an important research area in computer vision and image processing. In recent years, deep learning has emerged as a powerful tool for enhancing low light images, with convolutional neural networks (CNNs) being the most used architecture. In this study, we propose a deep learning approach for enhancing low light images using a modified CNN. Our approach involves training the network on a large dataset of low light images and their corresponding enhanced images and using the trained model to enhance new low light images. We also propose a new loss function that encourages the network to enhance details and reduce noise in the images. Our experiments show that our approach outperforms existing state-of-the-art methods in terms of both objective metrics and visual quality, making it a promising technique for real-world low light image enhancement applications