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

Sparse constraint SAR image reconstruction regularization parameter GCV golden section automatic search algorithm

A technology of image reconstruction and sparse constraints, applied in image data processing, graphics and image conversion, computing, etc., can solve problems such as difficult construction, and achieve the effect of small amount of calculation

Inactive Publication Date: 2016-10-26
SOUTHWEAT UNIV OF SCI & TECH
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0028] For larger problems, due to computer memory limitations, will be difficult to construct

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
  • Sparse constraint SAR image reconstruction regularization parameter GCV golden section automatic search algorithm
  • Sparse constraint SAR image reconstruction regularization parameter GCV golden section automatic search algorithm
  • Sparse constraint SAR image reconstruction regularization parameter GCV golden section automatic search algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] In order to make the technical means, creative features, work flow, and use methods of the present invention achieve the purpose and effect easy to understand, the present invention will be further described below.

[0045] The present invention determines the sparse constraint SAR image reconstruction regularization parameter GCV golden section automatic search optimization algorithm as follows:

[0046] (1) Determine an initial interval . Note that it is common to start with a large initial interval, such as ;

[0047] (2) According to the golden ratio , determine the two test values . because The coverage area is large, so in the specific operation, the golden section point is selected on a logarithmic scale, that is, , ;

[0048] (3) calculation and ;

[0049] (4) Determine a new interval through the golden section search ,Right now

[0050] if ,in is a small normal number

[0051] So

[0052] otherwise ;

[0053] (5) , repeat s...

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 sparse constraint SAR image reconstruction regularization parameter GCV golden section automatic search numerical computation method. During regularization image reconstruction, selection of regularization parameters is a very important issue; for the selection of the nonquadratic regularization parameters, a conventional selection method is limited; and in order to obtain a high-quality reconstructed image, the regularization parameters are always selected manually. In order to solve the problems above, the invention provides the sparse constraint SAR image reconstruction regularization parameter GCV golden section automatic search numerical computation method on the basis of studying the GCV method. The beneficial effects of the method are that automatic selection of the sparse constraint SAR image reconstruction regularization parameters is realized; calculation amount in calculating the sparse constraint SAR image reconstruction regularization parameters is small through the method, and a better balance is kept between noise suppression and feature preservation; and a more reasonable reconstructed image can be obtained.

Description

technical field [0001] The invention relates to a GCV golden section automatic search numerical calculation method for the regularization parameters of sparsely constrained SAR (Synthetic aperture radar, synthetic aperture radar) image reconstruction. Background technique [0002] In the regularized reconstruction of SAR images, the choice of regularization parameters is a very important issue, which directly determines the quality of the reconstructed image. At present, researchers have proposed several regularization parameter selection methods based on statistical ideas, among which the most famous and widely used is the Tikhonov regularization method. The Tikhonov regularization method is a quadratic regularization method. In the Tikhonov regularization method, the quadratic optimization problem consists of a set of linear equations with closed solutions, which can realize the automatic selection of regularization parameters and greatly reduce the image reconstruction. ...

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): G06T3/40
CPCG06T3/4053
Inventor 朱正为郭玉英楚红雨
Owner SOUTHWEAT UNIV OF SCI & TECH
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