Single image haze removal on complex imaging background

Jiang, Bo; Zhang, Wanxu; Meng, Hongqi; Ru, Yi; Zhang, Yongqin; Ma, Xiaolei

doi:10.1109/icsess.2015.7339055

Cited by 5 publications

(1 citation statement)

References 10 publications

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“…First of all, atmospheric light value is estimated, which is the furthest pixel rather than the brightest one in the original haze image ( ) according to [14]. On a foggy day, there is a large quantity of fog droplets suspending in the atmosphere.…”

Section: Dark Channel Prior and Image Of Scene Depth Proportionmentioning

confidence: 99%

Gray-Scale Image Dehazing Guided by Scene Depth Information

Jiang

Zhang

Jian

et al. 2016

Mathematical Problems in Engineering

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Combined with two different types of image dehazing strategies based on image enhancement and atmospheric physical model, respectively, a novel method for gray-scale image dehazing is proposed in this paper. For image-enhancement-based strategy, the characteristics of its simplicity, effectiveness, and no color distortion are preserved, and the common guided image filter is modified to match the application of image enhancement. Through wavelet decomposition, the high frequency boundary of original image is preserved in advance. Moreover, the process of image dehazing can be guided by the image of scene depth proportion directly estimated from the original gray-scale image. Our method has the advantages of brightness consistency and no distortion over the state-of-the-art methods based on atmospheric physical model. Particularly, our method overcomes the essential shortcoming of the abovementioned methods that are mainly working for color image. Meanwhile, an image of scene depth proportion is acquired as a byproduct of image dehazing.

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Section: Dark Channel Prior and Image Of Scene Depth Proportionmentioning

confidence: 99%