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

Edge significance-based EFMT multi-sensor image registration method and system

A technology of edge images and heterogenous images, applied in the image field, can solve the problems of reduced correlation peak significance, mismatch, large registration error, etc.

Inactive Publication Date: 2015-04-22
BEIJING UNION UNIVERSITY
View PDF2 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method also has some inherent problems: first, this method is still applicable to images with rich grayscale information; second, when there is rotation, the correlation peak is significantly reduced, and the position of the correlation peak is not reliable corresponding to the correct matching parameters; Simple translation transformation has large registration error or even mismatch

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
  • Edge significance-based EFMT multi-sensor image registration method and system
  • Edge significance-based EFMT multi-sensor image registration method and system
  • Edge significance-based EFMT multi-sensor image registration method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0041] Such as figure 1 Shown is a schematic flow chart of the traditional FMT registration algorithm in the prior art. This method is an image registration method based on Fourier-Mellin transform (abbreviated as FMT algorithm) proposed by Chen et al. in 1994. It calculates two images Calculate the relative translation of the peak positions corresponding to the inverse Fourier transform of the cross power spectrum, and use the rotation and scale characteristics of the Fourier transform in the Log-polar space by performing logarithmic-polar coordinate (Log-polar) transformation on the image amplitude spectrum Find the rotation angle and scaling factor between images. Through a large number of experiments on remote sensing images, medical images, target recognition and tracking and other applications, Reddy et al. have proved that this method has the advantages of high precision and fast speed, but it is also effective for changes in illumination, different image content, occlu...

Embodiment 2

[0050] Such as image 3 Shown is a flow chart of another preferred embodiment of the EFMT heterogeneous image registration method based on edge saliency according to the present invention. It includes in turn: extracting the edge of the reference image R and the image S to be registered to obtain a binary edge image; transforming the edge image into the Log-polar domain to obtain LPr and LPs; performing cross-power spectrum calculation on LPr and LPs; calculating the Rotation angle and scale factor; perform inverse transformation on the image to be registered to obtain the righting image; perform phase correlation calculation based on the reference edge image and the righting edge image to obtain the translation amount; perform translation transformation on the rotated righting image according to the translation amount to obtain the registered image.

[0051] Specifically, step 1. Extract edges from the reference image R and the image to be registered S to obtain a binary edg...

Embodiment 3

[0078] This embodiment provides a heterogeneous image registration system, the system includes the following modules:

[0079] The edge extraction module is used to extract the edge image of the reference image and the image to be registered and the edge image of the transformed image;

[0080] A calculation module, for transforming the edge image into the logarithmic-polar coordinate domain, and calculating the phase correlation of the logarithmic-polar coordinate domain, obtaining the rotation angle and scale factor of the image and calculating the translation parameters of the image;

[0081] An image transformation module, the image transformation module performs image transformation on the image to be registered according to the rotation angle and scale factor, and performs translation transformation on the righting image according to a translation parameter.

[0082] Wherein, the edge extraction module further includes a time-domain edge detection module, and the edge im...

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 edge significance-based EFMT multi-sensor image registration method and system. The method comprises the following steps that a, an edge extraction module is used for extracting a reference image and an edge image of a to-be-registered image; b, a calculation module is used for converting the edge image to a log-polar coordinate domain, and calculating phase correlation of the log-polar coordinate domain image to obtain a rotation angle and a scale factor of the image; c, an image conversion module is used for converting the to-be-registered image according to the rotation angle and the scale factor, and the edge extraction module is used for extracting the edge image of the converted image; and d, the calculation module is used for calculating the edge image conversion in the step c, the phase correlation and the rotation angle of the edge image of the reference image in the step a to obtain an image transition parameter. According to the scheme, based on a traditional registration algorithm, the FMT conversion is carried out by utilizing the edge image of images, and the accuracy and speed of multi-sensor image registration are improved.

Description

technical field [0001] The invention relates to the image field, in particular to an EFMT heterogeneous image registration method and system based on edge saliency. Background technique [0002] Image registration is an important step in practical applications such as multi-source data fusion, temporal image analysis, object detection, pattern recognition, and image mosaicing. With the continuous expansion and improvement of image acquisition methods and technologies, the problems of low registration accuracy, low success rate, and poor real-time performance in image registration have become increasingly prominent. Especially the registration of heterogeneous images has always been a difficult point in the registration field. [0003] The biggest problem with heterogeneous images is that they record the reflection characteristics of the same target or scene in different bands. Due to the different imaging mechanisms, the grayscale performances presented are very different, ...

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): G06T7/00G06T3/00
Inventor 章学静李月琴张军刘元盛
Owner BEIJING UNION UNIVERSITY
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