Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Binocular visual image super-resolution fusion de-noising method

A super-resolution, binocular vision technology, applied in the field of image processing, can solve the problem of local position matching and other problems

Active Publication Date: 2016-08-10
XIDIAN UNIV
View PDF5 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art, and propose a binocular image super-resolution method to solve the problem that the local positions cannot be matched, and at the same time enhance image details and reduce image noise

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
  • Binocular visual image super-resolution fusion de-noising method
  • Binocular visual image super-resolution fusion de-noising method
  • Binocular visual image super-resolution fusion de-noising method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0097] The present invention will be further described below in conjunction with the accompanying drawings.

[0098] Refer to attached figure 1 , the specific embodiment of the present invention is described as follows.

[0099] Step 1, input the binocular image to be super-resolution fusion.

[0100] Input the binocular image to be super-resolution fused, where the image captured by the left camera is the left grayscale image, and the image captured by the right camera is the right grayscale image.

[0101] Step 2, global position registration image;

[0102] (2a) Using the scale-invariant feature transformation SIFT method to process the left grayscale image and the right grayscale image to obtain the feature points of the left grayscale image and the feature points of the right grayscale image;

[0103] The specific steps of the scale-invariant feature transformation SIFT method are as follows:

[0104] Step 1: For the left grayscale image and the right grayscale image,...

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 binocular visual image super-resolution fusion de-noising method, comprising steps of (1) inputting a binocular image to be subjected to super-resolution fusion, (2) performing global position image registration, (3) performing local position image matching, (4) updating the binocular image, (5) performing image super-resolution fusion, (6) performing image de-noising, and (7) outputting a final high resolution image. In the image registration process, a local position registration method is added, a Laplace operator is applied to the image super resolution fusion, and a non-local mean value filtering method is employed to perform de-noising on the fusion image. The binocular visual image super-resolution fusion de-noising method overcomes the deficiencies in the prior art that image local positions are not matched, detail enhancement is not enough and the function of noise inhibition is absent. The binocular visual image super-resolution fusion de-noising method obtains a super resolution fusion image which has enhanced image details and reduced noise.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a binocular vision image super-resolution fusion denoising method in the technical field of image super-resolution. The present invention can be applied to image post-processing of intelligent terminal equipment or professional camera equipment. Background technique [0002] The image super-resolution fusion method of binocular vision refers to the left grayscale image and right grayscale image of the same scene obtained from the binocular camera, using their temporal and spatial correlation and information complementarity, using reconstruction technology Image super-resolution fusion. The reconstruction technology assumes that the super-resolution image is under appropriate deformation, translation, sub-sampling and noise interference, and uses multiple frames of low-resolution images as data consistency constraints, and combines image prior knowledge to solve th...

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
IPC IPC(8): G06T7/00G06T3/40G06T5/50
CPCG06T3/4053G06T5/50G06T2207/10004G06T2207/20192G06T2207/20221
Inventor 宋彬杨荣坚曹茸李莹华秦浩
Owner XIDIAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com