Image dehazing is a scenic enhancement technique used to counteract meteorologically induced diminished visibility. The sort, size, and concentration of the particles have an impact on the haze or fog problem, which is primarily caused by unfavorable weather and climate circumstances. The picture dehazing technique is used to get rid of the smoke, dust, and fog. From blurry photos, scientists and researchers try to recover crisp, high-quality images. Before the introduction of deep learning, image dehazing methods relied mostly on several historical theories and atmospheric scattering models. These days, picture dehazing is one area where deep learning approaches have evolved. Based on the CNN, other machine learning models, and deep learning models, the picture dehazing is possible for producing an image with clarity and a haze-free image. In real-life situations, computer vision systems can benefit from technology that addresses challenging environmental conditions. In a variety of applications, including surveillance, automotive, remote sensing, and more, dehazing images using deep learning can significantly improve visibility, image quality, and performance.