Low-light photography often suffers from issues such as noise, low contrast, and color distortion due to insufficient lighting, resulting in images that do not accurately capture the scene. This paper explores various advanced techniques for enhancing images taken in low-light conditions. We examine traditional methods, such as histogram equalization and Retinex theory, as well as state-of-the-art deep learning approaches.