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September 15, 2010IEEE Transactions on Pattern Analysis and Machine Intelligence6,247 citations

Single Image Haze Removal Using Dark Channel Prior

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KHKaiming HeJSJian SunXTXiaoou Tang

Key Points

  • The aim is to develop an effective method for haze removal from single images using the dark channel prior.
  • Introduced dark channel prior based on statistics of outdoor haze-free images.
  • Estimated haze thickness using the haze imaging model.
  • Recovered high-quality haze-free images from input images.
  • Successfully demonstrated the effectiveness of haze removal on various hazy images.
  • Achieved high-quality depth maps as a byproduct of the haze removal process.

Abstract

In this paper, we propose a simple but effective image prior-dark channel prior to remove haze from a single input image. The dark channel prior is a kind of statistics of outdoor haze-free images. It is based on a key observation-most local patches in outdoor haze-free images contain some pixels whose intensity is very low in at least one color channel. Using this prior with the haze imaging model, we can directly estimate the thickness of the haze and recover a high-quality haze-free image. Results on a variety of hazy images demonstrate the power of the proposed prior. Moreover, a high-quality depth map can also be obtained as a byproduct of haze removal.

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Cite This Study

He et al. (2010) studied this question.

synapsesocial.com/papers/69ce23856b0ac1c563d18585https://doi.org/10.1109/tpami.2010.168
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