A Survey of Image Enhancement and Dehazing Algorithms to Improving Autonomous Navigation in Fog and Dust.

Abstract

Video captured during sand-dust weather conditions indicates significant degradation, diminished contrast, and pronounced color distortion. The reason behind this phenomenon is the impact of sand-dust particles, which result in the dispersion and assimilating of light. Consequently, resultant image seems blurred and lacks contrast. Additionally, the alteration in color is attributed to the swift reduction of blue light. Adverse weather circumstances, such as fog, sand, and dust storms, cause problems with vision for deploying self-driving automobiles. To guarantee secure and seamless operations during frequent adverse weather conditions, video enhancement plays a vital role in facilitating vehicular mobility and navigational in both road and air transportation. To improve the safety and efficiency of operation, it is imperative to employ video dehazing techniques, particularly in adverse weather conditions. The purpose of our overview is to offer interested researchers a thorough and methodical examination of image enhancement approaches, serving as an important point of reference for their work. The text explored different image enhancement methods, along with the challenges, constraints, advantages, and drawbacks associated with using these techniques throughout the past five years. Specifically, it focused on three aspects: supervised algorithms, unsupervised algorithms, and quality evaluation.