Image Dehazing Framework Using Brightness-Area Suppression Mechanism

  • Shengkui DaiEmail author
  • Xiangcheng Chen
  • Ziyu Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11901)


Since more and more outdoor images are often degraded by haze and suffer from bad visibility, haze removal has become an important task of image restoration in recent decades. A systematic dehazing framework based on Koschmieder model is proposed in this paper, which adopts a novel brightness-area suppression mechanism. Firstly, global brightness-area suppression blending the large-scale atmospheric veil with the result of edge-preserving filtering, could protect the white objects not becoming darker. Then, the local brightness-area suppression based on sky detection could prevent the sky region from over saturation. In addition, post-processing procedures are designed in this dehazing system in order to generate haze-free image with better visual perception. This framework is on-limits and extensible, in that, it can accept other better dehazing technique as one of the core steps inside. Experiments show that the performance of this framework outperforms multiple state-of-the-art dehazing algorithms.


Brightness suppression Transmission Dehazing Haze removal Image restoration 



This work is supported by Science and Technology Planned Project of Quanzhou (No. 2018C016). We thank the referees for their comments and suggestions which make the paper much improved.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.College of Information Science and EngineeringHuaqiao UniversityXiamenChina

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