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Image defogging method based on dark channel prior and adaptive histogram equalization

A technique of histogram equalization and dark channel prior, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of image detail loss, color distortion, etc., to achieve accelerated estimation, natural color, and color distortion resolution. Effect

Inactive Publication Date: 2019-05-21
MINJIANG UNIV
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Problems solved by technology

[0008] The purpose of the present invention is to provide a method based on dark channel prior and adaptive histogram to solve the problem of color distortion in bright areas such as the sky and image detail loss due to dark channel prior based image defogging algorithm. Image equalization image defogging method, which significantly improves the effect and speed of image defogging

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  • Image defogging method based on dark channel prior and adaptive histogram equalization
  • Image defogging method based on dark channel prior and adaptive histogram equalization
  • Image defogging method based on dark channel prior and adaptive histogram equalization

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[0055] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0056] The present invention provides an image defogging method based on dark channel prior and adaptive histogram equalization, comprising the following steps:

[0057] Step S1. Obtain the fog image as the input image, and use the quadtree algorithm to estimate the atmospheric light value in the atmospheric scattering model; where the atmospheric scattering model is:

[0058] I(x)=J(x)t(x)+A(1-t(x)) (1)

[0059] In the formula, x represents the position of the pixel point; I represents the observed foggy image; t represents the transmittance; J represents the fog-free image;

[0060] The specific implementation steps of the quadtree algorithm to estimate the atmospheric light value in the atmospheric scattering model are as follows:

[0061] Step S12, dividing the input image into 4 image blocks;

[0062] Step S12, selecting the image...

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Abstract

The invention relates to an image defogging method based on dark channel prior and adaptive histogram equalization. The method comprises the following steps: firstly, acquiring a fog image as an inputimage, and estimating an atmospheric light value in an atmospheric scattering model by adopting a quadtree algorithm; Secondly, estimating the simplified image transmissivity according to the atmospheric light value; Then, the estimation of the transmissivity is optimized by using a tolerance error correction mechanism; Substituting the optimized transmissivity estimation value into an atmospherescattering model to derive an initial defogging result of the image; And finally, enhancing the defogging result by using a contrast-limited adaptive histogram equalization algorithm (CLAHE) to obtain a final defogging result. The image defogging method based on dark channel prior solves the problems of color distortion and dark brightness of an image defogging algorithm based on dark channel prior, and the defogged image is richer in details and natural in color.

Description

technical field [0001] The invention relates to an image defogging method based on dark channel prior and adaptive histogram equalization. Background technique [0002] With the aggravation of air pollution, the frequency of smog weather is getting higher and higher. In foggy weather, fine particles and water droplets suspended in the atmosphere will absorb, scatter and refract light, making the image scene generated in foggy days unclear and image details lost, limiting the use of foggy weather images and videos in traffic monitoring, Applications in areas such as target tracking and autonomous navigation. For this reason, the clear processing of foggy images is very important. Image defogging is a kind of technology that studies the sharpening of foggy images. In recent years, researchers have proposed a series of image defogging algorithms. These image defogging algorithms can be roughly divided into two categories: methods based on image enhancement and methods based...

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Application Information

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IPC IPC(8): G06T5/00G06T5/40G06T7/90
Inventor 李佐勇周常恩胡俊鹏杨峰刘伟霞李灿东
Owner MINJIANG UNIV
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