While the dark channel prior algorithm works well for single image haze removal

it has to take long time to proces and require expensive computational overhead and huge memory resource.In this paper

we propose a fast daze removal algorithm based on dark channel prior knowledge.In the proposed approach

edge substitution method is developed to take place of the original soft-matting operator

which will substantially reduce the computational complexity.To deal with the invalid case of the dark channel

we exploit a scheme to identify bright area based on dual threshold and develop a way to correct transmission rate

which enables the dark channel prior to be more applicable.Additionally

enhanced processing is introduced by adopting nonlinear contrast stretching

thus improving the visual effect of defogging images.Several numerical experiments demonstrate that the proposed approach outperforms the original algorithm in daze removal effect at a much lower implementation cost.