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Method for detecting SAR image changes based on neighborhood clustering kernels

An image change detection and clustering technology, applied in the field of image processing, can solve the problem of not making full use of unlabeled sample information and low detection accuracy, and achieve the effect of improving accuracy and comprehensive extraction.

Inactive Publication Date: 2013-12-18
XIDIAN UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to address the shortcomings of the above-mentioned existing problems, and propose a SAR image change detection method based on the neighborhood clustering kernel to solve the detection accuracy caused by the existing difference synthesis kernel that cannot make full use of the unlabeled sample information low problem

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  • Method for detecting SAR image changes based on neighborhood clustering kernels
  • Method for detecting SAR image changes based on neighborhood clustering kernels
  • Method for detecting SAR image changes based on neighborhood clustering kernels

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Embodiment Construction

[0030] refer to figure 1 , the concrete implementation of the present invention comprises following training step and testing step:

[0031] 1. Training steps:

[0032] Step 1. For the original two-temporal SAR image X i , to extract its intensity features and texture features , i=1,2.

[0033] 1.1) Extract the original two-temporal SAR image X i The gray value vector of , and use the gray value vector as the intensity feature

[0034] 1.2) For the original two-temporal SAR image X i Carry out the Gabor transformation of C scales and D directions, so that Indicates the transformation coefficient of the two-temporal image on the s-th scale and the d-th direction, where s=1,...,C, d=1,...,D, then take (p,q) as Central pixel, extract high-pass subband coefficients on a window of size N The mean information of and variance information

[0035] μ X i s , ...

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Abstract

The invention discloses a method for detecting SAR image changes based on neighborhood clustering kernels. The method mainly solves the problems that no-label sample information can not be utilized by an existing method for synthesizing kernels based on differential values and lower detection precision is caused. The method includes the first step of extracting strength features and textural features of two time phase images, the second step of manually selecting label training samples and no-label training samples, the third step of building differential synthetic kernels by the utilization of the label training samples, the fourth step of correcting the differential synthetic kernels by utilization of the no-label training samples to obtain the neighborhood clustering kernels, the fifth step of inputting the neighborhood clustering kernels into a support vector machine to carry out training, and obtaining a support vector classifier, the sixth step of inputting the label training samples and the neighborhood clustering kernels formed by all pixel points into the support vector classifier to carry out testing, and obtaining a final change detection result. Compared with the method for synthesizing the kernels based on the differential values, the method for detecting the SAR image changes has the advantages of being high in detection precision, good to speckle noise resistance of the SAR images, and capable of being used in SAR image change detection.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to image change detection, and can be used for monitoring and evaluating ground object state changes on SAR images. Background technique [0002] SAR image change detection is a technology that uses SAR images in different periods to obtain information about changes in ground features. It is a data analysis method established for the characteristics of SAR images and can be used to identify changes in the state of ground features. Due to the increasing demand for SAR image change detection in the fields of natural disaster monitoring and assessment, resource and environmental monitoring, military target detection, and crop monitoring, the SAR image change detection method with high detection accuracy and high execution efficiency has become a current research hotspot. [0003] SAR image change detection methods can generally be divided into: change detection methods based on dir...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/66G06T7/00
Inventor 李明贾璐吴艳张鹏刘高峰陈洪猛安琳
Owner XIDIAN UNIV
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