• Chintan Dave
• Hetal Patel

Haze formation is caused by tiny particles suspended in the air that scatter light coming from the scene. As light travels through the atmosphere, it can interact with molecules and particles. The tiny particles, like dust, smoke, or water droplets, bend the light rays in different directions. The scattered light from haze particles creates a whitish or greyish veil across the image, reducing the contrast and color fidelity of the images. Many computer vision tasks rely on clear and accurate image data. Haze disrupts this by obscuring objects and reducing their visibility. Image dehazing improves the quality of the image data, allowing computer vision algorithms to perform tasks like object detection, recognition, and scene understanding more effectively. Real-time applications like self-driving cars heavily rely on image dehazing to avoid accidents in bad weather. The paper summarizes the current state-of-the-art single image dehazing methods and classifies them according to their groups. The paper analyze the methods, significant techniques, and models used to improve the image dehazing task. To conclude, the paper provides a comprehensive comparison of various image dehazing techniques. This comparison includes both quantitative and qualitative evaluations of each method’s performance. Additionally, the paper highlights the key strengths and limitations associated with each dehazing approach.

Single image dehazing, supervised learning, unsupervised learning, generative adversarial network, MRF

"In-depth Investigation of Single Image Dehazing Methods and their variants: An Extensive Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.i577-i584, March-2024, Available :http://www.jetir.org/papers/JETIR2403874.pdf

"In-depth Investigation of Single Image Dehazing Methods and their variants: An Extensive Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppi577-i584, March-2024, Available at : http://www.jetir.org/papers/JETIR2403874.pdf