Automobile night vision anti-halo image segmentation and evaluation method based on infrared and visible light fusion

A fusion image and image segmentation technology, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as poor evaluation results and inconsistent visual effects of human eyes, and achieve a reasonable evaluation effect

Active Publication Date: 2019-01-08
XIAN TECH UNIV
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Problems solved by technology

[0010] The invention provides a car night vision anti-halation image segmentation method and a fusion image evaluation method of infrared and visible light fusion, the method solves the problem that the existing infrared and visible light fusion image evaluation method is used to evaluate the car night vision anti-halation fusion image , the evaluation results are inconsistent with the visual effect of the human eye, and the more thorough the halo removal of the fusion image is, the worse the evaluation result is. It is used to evaluate the degree of halo removal and image detail quality of the anti-halation fusion image at night

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  • Automobile night vision anti-halo image segmentation and evaluation method based on infrared and visible light fusion
  • Automobile night vision anti-halo image segmentation and evaluation method based on infrared and visible light fusion
  • Automobile night vision anti-halo image segmentation and evaluation method based on infrared and visible light fusion

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Embodiment

[0127] Simulation conditions of this embodiment: Windows7 operating system, MATLAB software.

[0128] Main content: Automatically determine the halo critical gray value of the visible light grayscale image by using the adaptive iterative threshold method, and automatically divide the visible light, infrared and fusion images into halo and non-halo areas, and calculate the halo elimination of the halo area Evaluate the halo elimination degree of the fused image, and calculate the evaluation index of the fused image in the non-halation area to evaluate the color detail information enhancement effect of the fused image. Specific steps:

[0129] 1. Partition:

[0130] 1. Use the imread function to read visible light, infrared and fused three images (see figure 1 , figure 2 , image 3 );

[0131] 2. Use the rgb2gray function to convert the visible light color image into a grayscale image;

[0132] 3. According to the formulas (4), (5), and (6), the image is divided into the ...

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Abstract

The invention provides an automobile night vision anti-halo image evaluation method based on infrared and visible light. The method automatically determines a halo threshold gray value of a visible light gray image according to halo degree of visible light image by designing adaptive iterative threshold method, and automatically divides the fused image into a halo region and a non-halo region. Aiming at the difference between halo region and non-halo region, the halo elimination degree is designed to evaluate the effect of halo elimination in halo region, and the enhancement effect of color detail information in non-halo region is evaluated from multiple angles. This method solves the problem that the evaluation result of infrared and visible fusion image is inconsistent with human visualeffect when it is used to evaluate automobile night vision anti-halo fusion image, and the halo elimination of fusion image is more thorough and the evaluation result is worse.

Description

technical field [0001] The invention belongs to the field of automobile anti-halation technology, and in particular relates to a car night vision anti-halation image segmentation method and an image evaluation method after segmentation by combining infrared and visible light. The degree of elimination and the quality of image details are suitable for judging the fusion algorithm of automobile anti-halation image combining infrared and visible light. Background technique [0002] The image fusion anti-halation technology, which combines the advantages of no halo in infrared images and rich color detail information in visible light images, provides a new way to solve the problem of halo in night driving, and has a good application prospect. [0003] In order to judge the halo elimination degree and detail information enhancement effect of automobile night vision anti-halation fusion images, as well as to judge the pros and cons of different image fusion algorithms, the evaluat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/11G06T5/00G06T7/136
CPCG06T5/009G06T2207/20221G06T7/11G06T7/136
Inventor 郭全民柴改霞高嵩田英侠杨建华马超周芸
Owner XIAN TECH UNIV
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