Journal of Jilin University(Engineering and Technology Edition) ›› 2019, Vol. 49 ›› Issue (4): 1377-1384.doi: 10.13229/j.cnki.jdxbgxb20180208

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Image dehazing algorithm by sky segmentation and superpixel⁃level dark channel

Ke⁃yan WANG1(),Yan HU1,Huai WANG2,Yun⁃song LI1   

  1. 1. State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an 710071, China
    2. 31668 Troops of the Chinese People's Liberation Army, Xining 810000, China
  • Received:2018-03-09 Online:2019-07-01 Published:2019-07-16

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Abstract:

In order to improve the quality of restored images, a single image dehazing approach based on sky segmentation and superpixel-level dark channel model is proposed. First, a simple but effective multi-threshold sky segmentation method is presented, which divides the image into sky area and non-sky area. Second, the atmospheric light is estimated in sky area. Third, the transmission maps of the two types of areas are estimated respectively. For sky area, the transmission is directly estimated by the linear relationship between the dark channel values of clear images and the corresponding hazy images. For non-sky area, the transmission is estimated by superpixel-level dark channel values. Finally, the haze-free image can be restored by the atmospheric scattering model. Experimental results show that, compared with the existing methods, the proposed method can segment the sky more accurately with better adaption of the thresholds, and can estimate the atmospheric light and the transmission map with higher accuracy and efficiency. Moreover, the dehazed images obtained by the proposed method have many advantages such as high contrast, natural color and abundant details.

Key words: information processing technology, image dehazing, transmission, dark channel prior, super?pixel

CLC Number: 

  • TN919.8

Fig.1

Architecture of proposed method"

Fig.2

Flow chart of sky segmentation"

Fig.3

Results of each step of transmission map estimation"

Fig.4

Visual comparison for sky segmentation results"

Fig.5

Comparison for different transmission estimation methods in sky area"

Fig.6

Comparison for dehazed images and atmospheric light estimation results"

Fig.7

Visual comparison for dehazed images"

Table 1

Statistical of quantitative evaluation"

评价指标 图 文献[3]结果 文献[7]结果 文献[8]结果

本文

结果
新增可见边之比 e

1

2

3

-0.1817

0.1250

0.4887

-0.4355

0.1432

0.3020

0.4645

0.1129

0.3120

0.4842

0.1517

0.4866
可见边梯度均值 r

1

2

3

1.0671

0.8624

1.2806

0.9397

0.6440

1.0272

1.1471

0.9443

1.0975

1.8351

1.3181

1.5168

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