Check patentability & draft patents in minutes with Patsnap Eureka AI!

Image Deblurring Method for Intelligent Traffic Surveillance Based on Visual Attention Mechanism

A visual attention mechanism and intelligent transportation technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of low intelligent level of traffic monitoring and management, difficulty in screening and processing massive traffic monitoring image information, etc. simple effect

Inactive Publication Date: 2021-06-29
XI'AN POLYTECHNIC UNIVERSITY
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide an intelligent traffic monitoring image deblurring method based on a visual attention mechanism, which solves the defect in the prior art that the screening and processing of massive traffic monitoring image information is difficult, and it is difficult to quickly screen and remove image blurring to provide high efficiency. The quality of traffic monitoring images leads to the problem of low intelligence level of traffic monitoring and management

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 Deblurring Method for Intelligent Traffic Surveillance Based on Visual Attention Mechanism
  • Image Deblurring Method for Intelligent Traffic Surveillance Based on Visual Attention Mechanism
  • Image Deblurring Method for Intelligent Traffic Surveillance Based on Visual Attention Mechanism

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0078] refer to Figure 8 , taking the blur removal of traffic monitoring images as an example, the specific steps are as follows:

[0079] Step 1. Generate a saliency map of the original traffic surveillance image.

[0080] As shown in Figure 2, it is a fuzzy original image of traffic monitoring. First, the RGB color space of the original image is converted into HSI color space, and the calculation formula is as follows:

[0081]

[0082]

[0083]

[0084] Secondly, extract the internal features of the image X after converting the color space, and calculate the inverse matrix A of the matrix A in the formula X=AS -1 , the solution inverse matrix separates the components of the local region pixel matrix into independent components. The image is divided into blocks, and the local area pixel matrix is ​​multiplied by the solution inverse matrix to obtain the base vector W of the local area pixel matrix = {w 1 ,w 2 ,...,w n}. The Gaussian kernel density estimation ...

Embodiment 2

[0116] For general color image deblurring as an example, the specific steps are as follows:

[0117] In this embodiment, FIG. 5 is an image before the color image is blurred by using the present invention. The blurred color image calculation saliency map step 1 is the same as that of Example 1, and the image before blur removal and its saliency map are respectively shown in Figure 5a and Figure 5b .

[0118] In step 2, the parameter values ​​for image segmentation using the contour features and texture features of the saliency map are the same as those in Example 1. The segmentation map, edge map and energy map obtained by image segmentation are shown in Figure 6a , Figure 6b and Figure 6c .

[0119] In step 3, the segmented image is deblurred, the process in this step 3 is the same as in embodiment 1, the image after deblurring and its saliency map results are shown in Figure 7a and Figure 7b , Figure 7a The edge information of the middle image is prominent, a...

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 discloses a method for deblurring an intelligent traffic monitoring image based on a visual attention mechanism. The steps include: step 1, generating a saliency map of an original traffic monitoring image, and converting a blurred original traffic monitoring image from RGB color space to HSI color space; then according to the scene information of the image, maximize the scene information to obtain the saliency map; step 2, use the contour features and texture features of the saliency map to segment the image, and obtain the segmentation map of the saliency map; step 3, deblur the segmented image Processing, the structure information diffusion function is used to deblur the segmented image of the saliency map, and finally a clear image after deblurring is obtained. The method of the invention has simple steps, occupies less memory space, and has remarkable effect after deblurring.

Description

technical field [0001] The invention belongs to the technical field of image deblurring processing, and relates to an intelligent traffic monitoring image deblurring method based on a visual attention mechanism. Background technique [0002] With the continuous improvement of the intelligent level of traffic monitoring and traffic management, the intelligent video surveillance technology based on traffic monitoring image processing, analysis and understanding has attracted more and more people's attention. However, during the actual shooting, transmission and storage of traffic monitoring images, they will be affected by imaging equipment, environment, noise and other factors, resulting in blurred images. The image motion blur caused by the relative motion between the objects and the inappropriate distance between the shooting object and the optical center of the camera cause the image defocus blur. These blurs will lead to the loss of important details of the traffic monito...

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 Patents(China)
IPC IPC(8): G06T5/00G06T7/12G06K9/62
CPCG06T7/12G06T2207/20021G06T2207/10016G06T2207/10024G06T2207/30232G06F18/23213G06T5/73
Inventor 赵雪青石美红朱欣娟高全力师昕白新国薛文生
Owner XI'AN POLYTECHNIC UNIVERSITY
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com