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Road video defogging method based on dichromatic reflection model and bilateral filtering

A dual-color reflection model and bilateral filtering technology, applied in the field of image processing, can solve problems such as image blurring, and achieve the effects of fast dehazing speed, improved dehazing effect, and shortened dehazing time.

Active Publication Date: 2017-05-31
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In order to solve the problem that the picture is blurred after using the existing image defogging method for defogging, the present invention

Method used

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  • Road video defogging method based on dichromatic reflection model and bilateral filtering
  • Road video defogging method based on dichromatic reflection model and bilateral filtering
  • Road video defogging method based on dichromatic reflection model and bilateral filtering

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specific Embodiment approach 1

[0056] A road video dehazing method based on a two-color reflection model and a bilateral filter, including the following steps:

[0057] Step 1, for the video of the road, determine whether the image in the video is in a foggy state;

[0058] Step 2. For the image in the fog state in the video, use the physical defogging model to determine the required parameters;

[0059] I(x)=J(x)t(x)+A(1-t(x))

[0060]

[0061] Among them, I(x) represents the pixel of the hazy image that needs to be dehazed; J(x) represents the pixel of the restored haze-free image; t(x) is the transmittance; A is the global atmospheric light component; The known condition is I(x), which requires the target value J(x); obviously, this is an equation with infinite solutions, so the parameters that need to be estimated are t(x) and A, so as to obtain a unique solution;

[0062] Step 3. For the image in the foggy state in the video, combine the two-color reflection model and the bilateral filter to find th...

specific Embodiment approach 2

[0066] The process of determining whether the image in the video is in a foggy state described in step 1 of the present embodiment includes the following steps:

[0067] Step 1.1, the video is divided into a frame of continuous images, then the images are mapped to the HSV color space, HSV represents hue, saturation and lightness; the color of the fog itself is white, if there is fog in the image, it will The saturation of the image is reduced, while the brightness is increased; if there is no fog in the image, the saturation in the image is large, but the brightness is small; according to the characteristics of the above fog, it can be detected whether there is fog in the image, so that Further defogging;

[0068] Step 1.2, counting the percentage of the number of pixels whose difference between V and S of each frame image is greater than 0 in the total pixels of the image; when the percentage is greater than the threshold, it means that there is fog in the image; otherwise, ...

specific Embodiment approach 3

[0075] The specific process of step 3 of the present embodiment includes the following steps:

[0076] The formula for the two-color reflection model is as follows:

[0077]

[0078]

[0079]

[0080]

[0081] Among them, I c is a foggy color image that needs to be dehazed; is the color diffuse reflection image; I S is the specular reflection image, corresponding to the image of the fog part; σ c Is the chromaticity, which is related to the color of the pixel; I c D is the diffuse reflection image corresponding to the r, g, and b channels;

[0082] Λc is diffuse reflection chromaticity; Λ max is the maximum value of the diffuse reflection chromaticity on the three channels of r, g, and b, that is, Λ max =maxΛc, because the diffuse reflection chromaticity cannot be obtained, so it is necessary to use the approximate diffuse reflection chromaticity λ c The maximum value λ on the three channels r, g, b max To estimate the maximum value Λ of the diffuse emiss...

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Abstract

The present invention provides a road video defogging method based on a dichromatic reflection model and bilateral filtering, relates to the field of image processing, and specifically relates to a video defogging method. The method comprises: firstly, for a video of a road, determining whether an image in the video is in a foggy state; for the image in the foggy state in the video, determining a desired parameter by using a physical defogging model; for the image in the foggy state in the video, finding a position of fog by combining a dichromatic reflection model with bilateral filtering, so as to estimate global atmospheric light component A and transmittance t(x); limiting a range of the transmittance to min(t(x), 0.1); and obtaining a pixel of a restored defogged image according to limitation to the range of the transmittance. The method provided by the present invention is used for defogging of videos or images.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a video defogging method. Background technique [0002] At present, many scholars have carried out research on video defogging and proposed related defogging algorithms. These methods are mainly divided into two categories: one is image enhancement based on image processing, and the other is based on physical models (mainly atmospheric scattering model) image restoration method. Classic fog image enhancement methods mainly include histogram equalization, homomorphic filtering, wavelet transform, and Retinex algorithm. The foggy image restoration method mainly studies the physical mechanism of foggy image degradation, establishes a foggy weather degradation model, and inverts the degradation process to obtain a fog-free image or an optimal estimation value of a fog-free image that has not been disturbed and degraded. Restoration methods usually use the polarization characteristic...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20028G06T2207/20182G06T5/73G06T5/70
Inventor 付方发王瑶徐伟哲王宇哲石金进牛娜蔡祎炜王进祥
Owner HARBIN INST OF TECH
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