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

Method for reducing speckles of synthetic aperture radar (SAR) image by combining dual-tree complex wavelet transform with bivariate model

A dual-tree complex wavelet and bivariate model technology, applied in the field of image processing, can solve the problems of loss of image details and edge information, insufficient speckle noise filtering, etc., and achieve the goal of enriching image edge and detail information and filtering speckle noise Effect

Active Publication Date: 2011-02-23
XIDIAN UNIV
View PDF4 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this dual-tree complex wavelet transform speckle reduction method does not fully consider the geometric characteristics of the image and the statistical properties of the SAR image in the complex wavelet domain and the local correlation between the coefficients. Insufficient removal, at the same time, the details and edge information of the image are partially lost

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
  • Method for reducing speckles of synthetic aperture radar (SAR) image by combining dual-tree complex wavelet transform with bivariate model
  • Method for reducing speckles of synthetic aperture radar (SAR) image by combining dual-tree complex wavelet transform with bivariate model
  • Method for reducing speckles of synthetic aperture radar (SAR) image by combining dual-tree complex wavelet transform with bivariate model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0019] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0020] Step 1, perform dual-tree complex wavelet decomposition on the input SAR original image.

[0021] The input original SAR image is denoted as I. The SAR image itself is an image polluted by speckle noise. Therefore, it is not necessary to add a random noise or noise of a certain characteristic to the original image as in the study of natural image denoising. The image is subjected to spot reduction processing, and the input original SAR image I is subjected to dual-tree complex wavelet decomposition to obtain one and one low-frequency image and J scales, each scale has 6 high-frequency images, and the complex of high-frequency images on scale j is The wavelet coefficient is denoted as y j

[0022] the y j =y r，j +i·y i，j (1)

[0023] where y r，j is the real part of the complex wavelet coefficient, y i，j is the imaginary part of the complex wav...

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 method for reducing the speckles of a synthetic aperture radar (SAR) image by combining dual-tree complex wavelet transform with a bivariate model, which mainly solves the problems that speckle noise cannot be well inhibited and part of edge information and detailed information are lost in the conventional method for reducing the speckles of the SAR image. The method comprises the following steps of: performing dual-tree complex wavelet decomposition on the original SAR image to obtain a real part and an imaginary part of a decomposition coefficient on each scale; solving the variance of a noise coefficient by using a non-logarithmic additive noise model; solving the edge variances of the real parts and the imaginary parts of the complex wavelet coefficient by using a local neighborhood window; solving a threshold contraction function by maximum posterior estimation and performing threshold contraction on the dual-tree complex wavelet decomposition coefficient; and performing dual-tree complex wavelet reconfiguration on the contracted coefficient to obtain an image of which the speckles are reduced. The method has the advantages of capability of effectively removing the speckle noise from the SAR image and high edge preserving performance, and can be used for reducing the speckles of the SAR images with abundant edge information and detailed information, particularly the airport, runway and road-containing SAR images.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to image noise suppression, in particular to a SAR image speckle reduction method in complex wavelet domain, which can be used for the suppression of speckle noise in synthetic aperture radar images. Background technique [0002] Synthetic Aperture Radar (SAR) is a high-resolution imaging radar. It has all-weather, multi-polarization, multi-view, multi-depression angle data acquisition capabilities and the ability to penetrate some ground objects. It is not only widely used in military affairs, but also has a large number of civil applications in agriculture, meteorology, topography, and disaster monitoring. Applications. However, since SAR emits coherent waves, these coherent waves undergo coherent effects with ground objects, especially the backscattering effect of ground objects, which causes the target echo signal to attenuate. This attenuation is manifested in the image ...

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 Applications(China)
IPC IPC(8): G06T5/00
Inventor 王爽焦李成李军凤宏晓侯彪钟桦缑水平田小林
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