Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

K-SVD (K-means singular value decomposition) speckle inhibiting method based on SAR (synthetic aperture radar) image local statistic characteristic

A technology of coherent speckle suppression and local statistics, applied in the field of image processing, it can solve a large number of speckle noise, edge blurring and other problems, and achieve the effect of wide applicability, clear edge texture and good radiation characteristics.

Active Publication Date: 2012-06-20
XIDIAN UNIV
View PDF2 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, for SAR images with a low number of views, the final result still has a lot of speckle noise and the edges will be blurred because the speckle noise will affect the training of the dictionary.

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
  • K-SVD (K-means singular value decomposition) speckle inhibiting method based on SAR (synthetic aperture radar) image local statistic characteristic
  • K-SVD (K-means singular value decomposition) speckle inhibiting method based on SAR (synthetic aperture radar) image local statistic characteristic
  • K-SVD (K-means singular value decomposition) speckle inhibiting method based on SAR (synthetic aperture radar) image local statistic characteristic

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] refer to figure 1 , the implementation of the present invention is as follows:

[0043] Step 1, take the sliding factor as s=1, and the size is The window of the input size is The SAR image I, such as figure 2 and image 3 As shown, the image overlapping block extraction operation is performed to obtain a set of overlapping block vectors where y i is the ith overlapping block vector, M is the number of overlapping block vectors, and

[0044] M = ( N - n + 1 ) 2 .

[0045] Step 2, for the set of overlapping block vectors Perform random sampling to obtain a training sample set where y i ' is the i-th training sample, M' is the number of training samples, and 0

[0046] Step 3. According to the redundant sparse representation image noise su...

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 K-SVD (K-means singular value decomposition) speckle inhibiting method based on SAR (synthetic aperture radar) image local statistic characteristic, mainly solving the problem that detail information such as edge, texture and the like is fuzzy in the traditional speckle inhibiting method. The method is realized in the following processes of: inputting an SAR image, extracting overlapped blocks in the SAR image to obtain an overlapped block vector set; then randomly sampling the overlapped block vector set to obtain a training sample set; carrying out SAR_KSVD dictionary training on a training sample to obtain a final training dictionary; carrying out SAR_OMP sparse coding on the overlapped block vector set under the condition of the final training dictionary to obtain a sparse coding coefficient; and obtaining a speckle inhibited image by utilizing the final training dictionary and the sparse coding coefficient according to the redundant sparse representation image noise inhibiting theory. By applying the method disclosed by the invention, speckle noise in a homogenous region can be effectively inhibited, brightness and edge texture of a target at a strong reflection point can be well maintained to be clear, and the method disclosed by the invention can be applicable to SAR images in the fields such as land resource monitoring, natural disaster analysis and the like.

Description

technical field [0001] The invention belongs to the technical field of image processing, specifically a dictionary training K-SVD coherent speckle suppression method based on the local statistical characteristics of SAR images, which can be used for synthetic apertures in many fields such as land resource monitoring, natural disaster analysis, and urban development planning. Radar SAR Image Analysis. Background technique [0002] Coherent speckle noise is an inherent characteristic of SAR images. These coherent speckles scattered randomly in SAR images will be mixed with smaller ground objects, seriously affecting the quality of the image, and causing great difficulties for the automatic interpretation of SAR images. . Therefore, in SAR image processing, SAR image coherent speckle suppression becomes the key, and it is also the basis for subsequent SAR image feature extraction, segmentation, and recognition. The goal of coherent speckle suppression technology is: how to ma...

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): G06T5/00G01S13/90
Inventor 侯彪焦李成孙慧芳刘芳张小华田小林公茂果
Owner XIDIAN 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
Eureka Blog
Learn More
PatSnap group products