Single Image Haze Removal Algorithm using Dual DCP and Adaptive Brightness Correction

Dual DCP 및 적응적 밝기 보정을 통한 단일 영상 기반 안개 제거 알고리즘

  • Kim, Jongho
  • 김종호
  • Received : 2018.08.16
  • Accepted : 2018.11.02
  • Published : 2018.11.30


This paper proposes an effective single-image haze-removal algorithm with low complexity by using a dual dark channel prior (DCP) and an adaptive brightness correction technique. The dark channel of a small patch preserves the edge information of the image, but is sensitive to noise and local brightness variations. On the other hand, the dark channel of a large patch is advantageous in estimation of the exact haze value, but halo effects from block effects deteriorate haze-removal performance. In order to solve this problem, the proposed algorithm builds a dual DCP as a combination of dark channels from patches with different sizes, and this meets low-memory and low-complexity requirements, while the conventional method uses a matting technique, which requires a large amount of memory and heavy computations. Moreover, an adaptive brightness correction technique that is applied to the recovered image preserves the objects in the image more clearly. Experimental results for various hazy images demonstrate that the proposed algorithm removes haze effectively, while requiring much fewer computations and less memory than conventional methods.


Haze removal;Dual DCP;Dark channel prior;Brightness correction;Image enhancement


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Supported by : 순천대학교