  In this paper, we propose the pyramid fusion dark channel prior (PF-DCP) for
single image dehazing. Based on the well-known Dark Channel Prior (DCP), we
introduce an easy yet effective approach PF-DCP by employing the DCP algorithm
at a pyramid of multi-scale images to alleviate the problem of patch size
selection. In this case, we obtain the final transmission map by fusing
transmission maps at each level to recover a high-quality haze-free image.
Experiments on RESIDE SOTS show that PF-DCP not only outperforms the
traditional prior-based methods with a large margin but also achieves
comparable or even better results of state-of-art deep learning approaches.
Furthermore, the visual quality is also greatly improved with much fewer color
distortions and halo artifacts.

Computer Vision and Pattern Recognition