Defocusing fuzzy kernel estimation method based on binocular stereoscopic vision

A technology of binocular stereo vision and defocus blur, which is applied in computing, computer parts, character and pattern recognition, etc., to achieve the effect of clear principles, accurate and reliable calculation results, and improved accuracy

Pending Publication Date: 2020-05-19
TIANJIN UNIV
View PDF0 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The above method is only suitable for defocus blur kernel estimation of monocular images, and cannot effectively use more information provided by binocular images for blur kernel estimation

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
  • Defocusing fuzzy kernel estimation method based on binocular stereoscopic vision
  • Defocusing fuzzy kernel estimation method based on binocular stereoscopic vision
  • Defocusing fuzzy kernel estimation method based on binocular stereoscopic vision

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0026] In order to make the technical solution of the present invention clearer, the specific implementation method of the present invention will be further described below in conjunction with the accompanying drawings.

[0027] Below to figure 2 (a), figure 2 The defocused binocular image shown in (b) is an example, and the specific processing process of the defocus blur kernel estimation method based on binocular stereo vision of the present invention is set forth:

[0028] 1. Initial blur kernel calculation steps:

[0029] will be like figure 2 (a), figure 2 The defocused binocular images shown in (b) are denoted as I 1 , I 2 , using the SAD-based local matching algorithm to calculate the disparity map P of the binocular image 0 , use the Canny edge detection algorithm to extract the edge pixels of the binocular image, and form the disparity value of the edge pixels into a set ψ k , where k=1, 2 represent the corresponding information of the left and right images...

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 a defocusing fuzzy kernel estimation method based on binocular stereoscopic vision. The method comprises the following steps: calculating an initial fuzzy kernel; acquiring anequivalent blurred image; carrying out three-dimensional matching calculation: synthesizing the gray information and the fuzzy kernel information as data items of an energy function of a global matching method, and performing three-dimensional matching on the same fuzzy image by optimizing the energy function by using the global matching method to obtain a dense disparity map; disparity post-processing: performing weighted mean filtering processing on the dense disparity map; and performing final fuzzy kernel calculation: taking the disparity map subjected to disparity post-processing as an initial disparity map, and performing fuzzy kernel calculation again to obtain a final fuzzy kernel. According to the method, the relation between parallax and the fuzzy kernel in binocular stereoscopic vision is fully considered, the accuracy of fuzzy kernel calculation is improved through the binocular image, and the method is suitable for defocusing fuzzy kernel estimation based on binocular stereoscopic vision.

Description

technical field [0001] The invention relates to a defocus blur kernel estimation method, in particular to a defocus blur kernel estimation problem based on binocular stereo vision. Background technique [0002] In the process of image acquisition, the imperfection of the imaging system and the interference of the external environment will cause the image to degrade to varying degrees. Defocus blur is a common form of blur, which refers to image blur caused by the depth of field of the imaging system or focusing errors. In addition, when imaging at a long distance, the image will be affected by atmospheric turbulence, which will also cause defocus blur. The above reasons make it difficult for the imaging system to collect clear images, and binocular images will have varying degrees of defocus, blur, and degradation, reducing the accuracy of 3D reconstruction. Whether it is a deblurring algorithm or a stereo matching algorithm for blurred images, the estimation of the blur k...

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): G06T7/593G06T7/13G06T7/80G06K9/62
CPCG06T7/593G06T7/13G06T7/80G06T2207/10012G06T2207/20228G06F18/23213
Inventor 陈则津葛宝臻陈雷
Owner TIANJIN UNIV
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