**5. Conclusions**

In this paper, we propose a haze-removal method using a normalised pixel-wise DCP method. We also propose a fast transmission map estimation by down-sampling and robust atmospheric-light estimation using a coarse-to-fine search strategy. Experimental results show that the proposed method can achieve haze removal with acceptable accuracy and greater efficiency than can conventional methods. The advantage of the proposed method is its fast computation with acceptable visual quality compared with state-of-the-art-methods. On the other hand, its disadvantage is that the user must set an appropriate *γ* manually for each different haze scene. How to systematically determine the appropriate *γ* value from the distribution of haze in the scene is our future work. In addition, we are going to apply the method to real applications, such as automatic-driving, underwater-robot and remotely sensed imaging [25].

**Author Contributions:** Conceptualization, methodology, software and analysis, Y.I.; investigation and software, N.H.; Conceptualization and validation, Y.-W.C. All authors have read and agree to the published version of the manuscript.

**Funding:** This research received no external funding

**Acknowledgments:** The authors would like to thank Enago (www.enago.jp) for the English language review.

**Conflicts of Interest:** The authors declare no conflict of interest.
