Low Light Image Enhancement Algorithm Based on Retinex and Dehazing Model

Abstract

Low light images often have low visibility, which not only affects the visual effect, but also reduces the performance of algorithms that require high-quality input. Aiming at the problem of low light image enhancement, this paper proposes a composite enhancement algorithm. Firstly, the dark channel prior model and retinex model are combined by two adjustable parameters to obtain a new enhancement model DeRetinex. Then, according to the duality of the dehazing model and retinex theory, the image of the previous step is inverted, and the DeRetinex model is used for the second enhancement, which can eliminate the haze caused by enhancement. Compared with the existing mainstream algorithms, the proposed algorithm has the advantages of avoiding over exposure, rich texture details, low noise and high color recovery.