Estimation method of image haze concentration

A haze concentration and haze technology, which is applied in the field of image processing, can solve the problems of large amount of calculation and many calculation features of haze concentration estimation

Inactive Publication Date: 2017-08-25
HUNAN UNIV
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Problems solved by technology

[0008] The present invention proposes a method for estimating image haze concentration, the purpose of which is to overcome the pr

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  • Estimation method of image haze concentration
  • Estimation method of image haze concentration
  • Estimation method of image haze concentration

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Embodiment Construction

[0041] The present invention will be further described below in conjunction with examples.

[0042] A method for estimating image haze density, comprising the following steps:

[0043] Step 1: Transform the input haze image from RGB space to HSV space, divide the haze image in HSV space into local blocks Ω of size r×r, and calculate the feature vector of each local block Ω;

[0044] The size r×r of the local block Ω ranges from 7×7 to 19×19;

[0045] The feature vector of each local block includes hue variance σ, Weber contrast mean w, and saturation mean

[0046] The normalization processing of the feature vector of each local block refers to:

[0047] σ n =k 1 ×(σ-min_σ)

[0048]

[0049] w n =k 3 ×(w-min_w)

[0050] Among them, max_f and min_f respectively represent the mean value of the first 0.1% feature values ​​with larger feature f, and the mean value of 0.1% feature values ​​with smaller feature values, f includes hue variance σ, Weber contrast mean w and s...

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Abstract

The invention discloses an estimation method of image haze concentration. The estimation method includes a first step of transforming the space, extracting local blocks, and calculating feature vectors; a second step of normalizing the feature vectors; and a third step of obtaining the haze concentration of an input haze image by using the respective relations of feature vectors of a clear image MVG model and a haze image MVG model with the normalized feature vectors of the local blocks of the input haze image. In the method, the concept of the feature vectors of the image local blocks is first proposed, the clear image MVG model and the haze image MVG model are introduced, the accurate local haze sensitive feature of each pixel in the haze image is obtained through adaptive calculation, and the haze concentration is estimated; in the calculation process, only the feature vector of each local block is required, and the calculated amount is small; and the method can be used for effectively perceiving the haze concentration without the need of a reference image, and meanwhile has the advantage of high calculation speed.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to a method for estimating image haze density. Background technique [0002] Image degradation in foggy days is mainly due to the serious absorption, scattering and reflection of light by molecules in the atmosphere, water vapor and aerosols composed of a large number of suspended particles, resulting in reduced atmospheric visibility, coupled with the influence of atmospheric turbulence, resulting in visible light The image color of the imaging system will become darker and the contrast will be reduced, which seriously affects the use of the imaging system. Therefore, it is of great significance to analyze the causes of haze, study the technology of defogging, and improve the visibility of images under haze weather conditions. [0003] Among them, the method of defogging and restoration based on physical model has been extensively studied because it utilizes the depth information a...

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T7/0002G06T2207/30192
Inventor 凌志刚邹文龚建伟
Owner HUNAN UNIV
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