Fast image dehazing based on multi-scale guided filtering

We propose a fast image dehazing algorithm based on multi-scale guided filtering. We first construct an image pyramid from a hazy input image. Then, based on the observation that the most time-consuming procedure is the estimation of the transmission map and atmospheric light, we estimate them only at the coarsest level. Then, we obtain the transmission map at the finest level by upsampling and guided image filtering. Experimental results show that the proposed algorithm is capable of real-time operation, while providing comparable or even better performance than the state-of-the-art algorithms.