Mine fog and dust image enhancement method based on dark channel prior and homomorphic filtering

A dark channel prior and homomorphic filtering technology, which is applied in image enhancement, image analysis, image data processing, etc., can solve the problems of high fog and dust concentration, uneven illumination, etc.

Inactive Publication Date: 2020-03-10
CHINA UNIV OF MINING & TECH (BEIJING)
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Problems solved by technology

[0005] The purpose of the present invention is to provide a method for image enhancement in coal mines,

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  • Mine fog and dust image enhancement method based on dark channel prior and homomorphic filtering
  • Mine fog and dust image enhancement method based on dark channel prior and homomorphic filtering
  • Mine fog and dust image enhancement method based on dark channel prior and homomorphic filtering

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[0062] In order to make the content and advantages of the technical solution of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings.

[0063] The present invention proposes a mine fog and dust image enhancement scheme based on a dark primary color prior model and homomorphic filtering, and the execution process is as follows:

[0064] The first step is to find the dark primary color map of the fog and dust image in the coal mine:

[0065] In computer vision and computer graphics, the fog and dust image formation model can usually be described by the following equation, where I (x, y) is the image to be defogged, and J (x, y) is the fog-free after defogging Image, A is the global atmospheric light component, t(x, y) is the transmittance:

[0066] I(x,y)=J(x,y)t(x,y)+A(1-t(x,y))

[0067] This empirical law is obtained by observing a large number of outdoor fog-free images and conducting statistical exp...

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Abstract

The invention discloses a mine fog and dust image enhancement method based on dark channel prior and homomorphic filtering. The mine fog and dust image enhancement method comprises the steps: 1,solving a dark channel image of a coal mine underground fog and dust image; 2, estimating atmospheric light by adopting a dark primary color value in an underground coal mine environment; 3, solving the rough transmissivity of the image according to the dark primary color graph; 4, obtaining a defogged image by using a defogged image restoration formula; and 5, processing the defogged and dedusted imageby adopting an improved homomorphic filtering scheme to obtain a final image. Compared with other existing underground coal mine fog and dust image enhancement methods, the definition of the fog anddust image can be effectively improved, the contrast ratio and details are enhanced, the influence of uneven illumination under a coal mine is reduced in a targeted mode, the image is close to original characteristics, the outline is clearer, and the enhancement effect is obvious when an area with a serious fog and dust phenomenon is processed.

Description

technical field [0001] The invention relates to the field of image enhancement, in particular to an image enhancement method for underground coal mines. Background technique [0002] Coal is the main energy source in my country. Coal mines are widely distributed in China. An important issue restricting the development of my country's coal industry is the safety of coal mine production. The development of coal mine automation and information technology is an inevitable choice for the coal mine safety production system. With the continuous popularization of intelligent video surveillance system and digital image acquisition equipment, using image technology to carry out safe production is a hot research direction in the development of coal mine industry. Although the use of image technology for safe production has incomparable advantages over traditional production technologies, the special environment in coal mines has brought severe challenges to the application of images in...

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T5/003G06T2207/10004G06T2207/20056
Inventor 刘晓阳吴迎旭
Owner CHINA UNIV OF MINING & TECH (BEIJING)
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