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An Adaptive Image Dehazing Method Based on Dark Channel Prior

A dark channel priori and self-adaptive technology, applied in image enhancement, image analysis, image data processing, etc., can solve problems such as poor operability and poor adaptive defogging effect, and achieve good visual effect and satisfy The effect of adaptive defogging requirements

Active Publication Date: 2019-02-01
UNIV OF SCI & TECH OF CHINA
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  • Summary
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  • Application Information

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Problems solved by technology

Since these two parameters are manually set and the parameters are different for different fog images, the effect of adaptive defogging is poor and the operability is not strong.

Method used

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  • An Adaptive Image Dehazing Method Based on Dark Channel Prior
  • An Adaptive Image Dehazing Method Based on Dark Channel Prior
  • An Adaptive Image Dehazing Method Based on Dark Channel Prior

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Embodiment Construction

[0074] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0075] The execution flow of an adaptive image defogging method based on dark channel prior in the present invention is as follows: figure 1 Shown:

[0076] Step 1): Obtain the fog image in RGB format.

[0077] Step 2): Save the channel with the smallest value in the three channels of the RGB image in the previous step to obtain the minimum value channel map.

[0078] Step 3): Perform minimum value filtering on the minimum value channel map to obtain a dark channel map.

[0079] Step 4): Obtain the atmospheric light value according to the dark channel map, and the selected rule here is: select the brightest point in the RGB fog image corresponding to 0.1% of the dark channel median value as the atmospheric light value of the image.

[0080] Step 5): Dehaze the minimum value channel. The specific method here is: use the dark channel to calcul...

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Abstract

The invention discloses an adaptive image defogging method based on dark channel prior. The steps include: 1) Calculate the overall defogging factor: find the minimum value channel of the fog image in RGB format, and perform dark channel based analysis on the minimum value channel. A priori dehazing process, the dehazing result of the minimum value channel is calculated. Determine the overall haze condition of the image based on the ratio of the minimum channel and the global standard deviation of its dehazing result, and calculate the overall dehazing factor ω0. 2) Calculate the local dehazing factor: Calculate the local standard deviation of the minimum channel, combined with the atmospheric light value and the overall defogging factor ω0, and calculate the local defogging factor ω(x). The present invention adopts a method that combines the whole and the local part to solve the defogging factor, and can automatically adjust the defogging factor parameters according to the fog situation of the image, determine the optimal fog removal degree, and can meet the adaptive defogging needs in various scenarios and restore the The image details are greatly enhanced, the visual effect is good, and the method is simple and effective.

Description

technical field [0001] The invention relates to the technical field of digital image processing, in particular to an adaptive image defogging method based on dark channel prior. Background technique [0002] In recent years, smog has appeared more and more frequently in major cities in my country, and some places are even shrouded in smog for most of the year. In 2013, only 5 days in Beijing were not smog days; in January of this year, 30 provinces and cities were enveloped in smog four times. When the smog is large, the visibility is reduced, which seriously affects the clarity of the pictures taken. [0003] Images taken in hazy weather will be seriously degraded due to the influence of atmospheric light, doped with a large amount of fog components, the overall image is grayish white, with less edge information, and the detectability is greatly reduced. Especially for images taken in dense fog, the loss of detail information is large, which is not conducive to computer p...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20004G06T5/73
Inventor 凌强陈春霖朱学俊李峰
Owner UNIV OF SCI & TECH OF CHINA