Phase related-sub-pixel matching method based on maximum-kernel-density estimation

A kernel density estimation and phase correlation technology, which is applied in the field of remote sensing images and can solve problems such as affecting the matching accuracy, difficult to accurately solve the phase angle, and large gross errors in the phase matrix.

Active Publication Date: 2014-07-23
TONGJI UNIV
View PDF0 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, there are still three problems in the existing phase correlation sub-pixel matching method: ① The phase matrix obtained by phase correlation usually contains large gross errors, and the traditional least squares fitting method is difficult to accurately solve the phase angle; ② image The oversampling

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
  • Phase related-sub-pixel matching method based on maximum-kernel-density estimation
  • Phase related-sub-pixel matching method based on maximum-kernel-density estimation
  • Phase related-sub-pixel matching method based on maximum-kernel-density estimation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is carried out on the premise of the technical solution of the present invention, and detailed implementation and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.

[0042] A phase-correlated sub-pixel matching method based on maximum kernel density estimation, which is a development of phase-correlated sub-pixel matching based on two-dimensional plane fitting. Its theoretical basis is the translation property of the two-dimensional Fourier transform, that is, the translation between the reference image and the image to be matched in the spatial domain can be expressed as the linear phase difference of the two-dimensional Fourier transform in the frequency domain. The phase angle matrix obtained by the phase correlation between images corresponds ...

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 phase related-sub-pixel matching method based on maximum-kernel-density estimation. The method is specifically as follows: 1. calculating an inter-image cross-power spectrum Q(u,v) is calculated; 2. separating a real part and an imaginary part of the Q(u.v) and applying phase edge filtering denoising to solve a phase angle matrix Psi(u,v); 3. unwrapping the phase angle matrix so as to obtain a corresponding plane matrix Psi unwrap(u,v); 4. using an MKDE method to perform fitting on the plane matrix so as to obtain plane equation parameters x0 and y0 and according to a proportion relation of the phase angle and an airspace pixel, obtaining a sub-pixel matching result. Compared with the prior art, the matching result is excellent in stability so that effects of gross errors on the plane fitting of the angle phase in the phase angle matrix can be prevented effectively so that the matching precision is improved and at the same time a pixel locking effect of the sub-pixel matching result is reduced significantly.

Description

technical field [0001] The invention relates to the field of remote sensing images, in particular to a phase correlation sub-pixel matching method based on maximum kernel density estimation. Background technique [0002] Sub-pixel precise matching of remote sensing images is one of the key technologies in the field of photogrammetry and remote sensing. Through sub-pixel matching between images, data such as stereo disparity, object displacement, and surface deformation field can be accurately obtained, which has extremely important applications in the fields of DEM generation, image fusion, and surface deformation monitoring. [0003] The sub-pixel matching method based on phase correlation has the characteristics of good anti-noise performance, little influence by image gray level, and high matching accuracy, and has received extensive attention in recent years. Among them, Hoge et al. used a method based on singular value decomposition (SVD) to decompose the phase matrix ...

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): G06T7/00
Inventor 童小华徐聿升叶真刘世杰李凌云陈杰
Owner TONGJI 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