Image dehazing method

An image and original image technology, applied in the field of image processing, can solve the problems of high processing time requirements, large storage resources and computing resources, long processing time, etc., and achieve the effects of shortening processing time, high bandwidth, and low delay

Inactive Publication Date: 2018-06-29
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF4 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In a system for public security applications, for single image defogging, if the dark channel prior method is used for the image, although it has a good defogging effect, the processing time is long and requires a lot of storage resources and computing resources.
However, in systems for public safety applications, the processing time is usually higher.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Image dehazing method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0022] In this embodiment, there are electronic eyes, MEC (Mobile Edge Computing) server, remote server and terminal. The electronic eye detects whether the original image is defogged, and then sends the original image and detection results to the MEC server. If there is no need to defog, the MEC server directly sends the original image to the remote server for storage, otherwise the MEC server performs defogging processing on the original image, and then sends the processed image to the remote server for storage.

[0023] like figure 1 The method for image defogging of the present invention shown, the steps include:

[0024] A. Defog detection: Obtain the dark channel map D of the original image taken by the electronic eye, the steps are: take the minimum component value of each pixel RGB component of the original image in the electronic eye, and store it in a same size as the original image In the grayscale image, the grayscale image is then divided into multiple windows o...

Embodiment 2

[0031] In this embodiment, there are electronic eyes, MEC (Mobile Edge Computing) server, remote server and terminal. The electronic eye only captures images, and then sends the captured original images to the MEC server, where the MEC server detects whether to defog or not. If there is no need to defog, the MEC server directly sends the original image to the remote server for storage, otherwise the MEC server performs defogging processing on the original image, and then sends the processed image to the remote server for storage. Steps include:

[0032] A. Defog detection: Obtain the dark channel image D of the original image taken by the electronic eye. The steps are: after the original image is taken by the electronic eye, the original image is sent to the MEC server. Take the minimum component value of each pixel RGB component of the original image in the MEC server, store it in a grayscale image of the same size as the original image, and then divide the grayscale image i...

Embodiment 3

[0039] In this embodiment, there are electronic eyes, a remote server and a terminal. After the electronic eye captures the image, it directly detects whether the original image is defogged in the electronic eye. If there is no need to defog, the electronic eye will send the original image to the remote server for storage, otherwise, after the electronic eye performs defogging processing, the processed image will be sent to the remote server for storage. Steps include:

[0040] A. Defog detection: Obtain the dark channel map D of the original image taken by the electronic eye, the steps are: after the electronic eye has taken the original image, take out the minimum component value of each pixel RGB component of the original image in the electronic eye, and store it into a grayscale image of the same size as the original image, and then divide the grayscale image into multiple windows with pixels of 15×15, and perform minimum value filtering on each of the windows, using the ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to an image dehazing method. The method comprises the steps that A, whether dehazing processing is needed or not is judged according to the accumulated value obtained after all pixel values of dark channel graphs D of original images and the original images are subtracted respectively, if not, the original images are output and the process ends, and otherwise, step B is started; B, a global atmospheric light value is acquired according to the dark channel graphs D and the original images; C, dark channel graphs D2 of new images are calculated after each pixel of the original images is divided by the global atmospheric light value, and a white picture and the pixel values of the dark channel graphs D2 are subtracted respectively to obtain a transmittance graph T1; D, the transmittance graph T1 is refined through steerable filtering to obtain a transmission rate graph T2; E, dehazed images are output through a haze graph formation model. The image dehazing method can effectively improve the image dehazing effect, simplify the dehazing processing process, greatly shorten image processing time and effectively improve the image processing efficiency.

Description

technical field [0001] The present invention relates to an image processing method, specifically an image defogging method, which is especially suitable for but not limited to an image defogging method for public security. Background technique [0002] At present, the systems for public safety applications in various cities can obtain the road surface conditions of the roads in real time through the electronic eyes all over the roads. As long as the electronic eye captures 3 / 4 of the face, it can accurately recognize the whole picture of the face. In addition to recognizing faces, the electronic eye also has the ability to recognize license plates and detect fake base stations within a radius of 2 kilometers. [0003] However, due to the refraction, reflection, self-absorption and self-imaging of floating water droplets in the atmosphere, the contrast of the image captured by the image acquisition system in foggy days is low, causing color distortion, and even causing the m...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T5/20G06T1/20
CPCG06T1/20G06T5/003G06T5/007G06T5/20
Inventor 孙国林徐荣
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap