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Single image haze removal method based on non-linear clustering

A clustering method and non-linear technology, applied in the field of computer vision, can solve problems such as edge effects and image color distortion, and achieve the effects of improving visual effects, avoiding edge effects, and avoiding color deviation

Inactive Publication Date: 2016-11-16
SOUTH CHINA UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0004] The invention solves the problems of image color distortion and edge effect caused by traditional defogging methods

Method used

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  • Single image haze removal method based on non-linear clustering
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  • Single image haze removal method based on non-linear clustering

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Embodiment

[0023] Such as figure 1 As shown, a single image defogging method based on nonlinear clustering includes the following steps:

[0024] S1 obtains a foggy RGB image, and converts the foggy RGB image into an HSV image, specifically:

[0025] The depth of the scene, fog concentration, brightness and saturation satisfy the relationship d(x)∝c(x)∝v(x)-s(x), then the original RGB image can be converted into an HSV image first, and d(x) = θ 0 +θ 1 v(x)+θ 2 s(x)+ε(x).

[0026] The S2HSV image is divided into blocks, and the depth map of each block is obtained according to the brightness and saturation of each block;

[0027] S3 classifies the depth map according to the nonlinear clustering method (K-means) according to the depth value from far to near, respectively as far class, middle class and near class;

[0028] In S4, due to the effect obtained from the dark channel prior defogging method, it is found that the contrast of the distant part of the output image is too high, an...

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Abstract

The invention discloses a single image haze removal method based on non-linear clustering. The method comprises the following steps of S1, obtaining a hazed RGB image, and converting the hazed RGB image into an HSV image; S2, blocking the converted image to obtain a depth map of each block; S3, clustering the depth images using the non-linear clustering method, outputting a far class, a middle class and a near class, calculating a perspective rate image of the far class, and calculating corresponding perspective rate images of the middle class and the near class according to an dark channel image of the RGB image; and S4, merging the obtained perspective rate images, calculating the atmospheric light value of a whole image, and outputting a haze removal image. The invention can effectively prevent the edge effect and the color deviation of a dark channel prior haze removal method.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a single image defogging method based on nonlinear clustering. Background technique [0002] With the continuous development of computer technology, software and hardware algorithms are changing with each passing day, it has become possible for computers to optimize foggy weather images, and put forward the definition, color reproduction and image realism of the output images after defogging. In the case of foggy weather, due to the high relative humidity in the air and the large number of dust particles in the atmosphere, as the distance between the camera and the real object increases, the scattering effect of the atmospheric particles will affect the imaging effect of the camera. The impact increases. The image captured by the camera has low contrast, low saturation, and color shift. This not only affects the visual effect of the image, but also seriously affects the computer un...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T5/73
Inventor 青春美胡逸伟禹凤张胜
Owner SOUTH CHINA UNIV OF TECH
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