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

A method for estimating deformation field of sar full-map based on multi-scale residual map regularization

A multi-scale, deformation field technology, applied in computing, scene recognition, computer parts, etc., to achieve the effect of improving matching accuracy, improving positioning accuracy, and uniform distribution

Active Publication Date: 2022-07-19
WUHAN UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the deficiencies of the existing full-image deformation field estimation (point-to-point registration) technology, the present invention proposes a full-image SAR deformation field estimation algorithm based on multi-scale residual image energy minimum regularization

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
  • A method for estimating deformation field of sar full-map based on multi-scale residual map regularization
  • A method for estimating deformation field of sar full-map based on multi-scale residual map regularization
  • A method for estimating deformation field of sar full-map based on multi-scale residual map regularization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0055] The technical solutions of the present invention will be further described below with reference to the accompanying drawings.

[0056] like figure 1 As shown, the technical scheme adopted in the present invention includes the following key parts and technologies:

[0057] Part 1: Dense and uniformly distributed control point pairs are generated and matched with high precision.

[0058] The present invention designs a new method on the generation and matching of dense control point pairs. First, we use a large number of SIFT points as candidate control point pairs, so use the SIFT operator to extract a large number of candidate point pairs. These feature points are relatively dense and relatively evenly distributed, and these points have the characteristics of rich local features.

[0059] The SIFT-based feature point extraction can be summarized as:

[0060] (1) Construction of scale space (2) Extreme point detection (3) Key point location (4) Main direction determi...

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 provides a SAR full-image deformation field estimation method based on multi-scale residual image regularization. First, a large number of local feature points extracted by the SIFT algorithm are used as candidate control points, and a control point generation strategy based on phase correlation and gradient refinement is designed. , to generate dense and relatively evenly distributed control point pairs; secondly, in the deformation field estimation stage, a distortion model based on multi-scale residual map regularization consistency point drift is designed to achieve point-to-point subpixel registration of the whole image. The invention introduces the residual graph regularization term on the basis of the consistency point drift algorithm, solves the shortcoming that the consistency point drift algorithm is easy to fall into the local minimum value, and can quickly converge to the global optimal solution.

Description

technical field [0001] The present invention relates to a high-precision (sub-pixel) full-image deformation field estimation (also called high-precision dense registration or full-image point-by-point registration) technology of a SAR image based on a reference image. This technology is a key technology in the field of remote sensing applications (image change detection, high-precision data fusion). In particular, it relates to a dense control point pair generation strategy (extraction, high-precision matching) and deformation field parameter estimation based on multi-scale residual map regularization consistency drift. Background technique [0002] With the development of remote sensing observation technology, high-resolution, multi-platform (satellite, near-Earth space, airborne), multi-source (SAR, optical, hyperspectral) remote sensing images are becoming more and more abundant, and multi-source image data are distributed with high precision in space and time. Related t...

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): G06V20/13G06V10/46G06V10/75G06K9/62
CPCG06V20/13G06V10/462G06V10/751
Inventor 于秋则倪达文雷震吴鹏杰胡海波
Owner WUHAN 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