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Time sequence PolSAR image unsupervised change detection method considering statistical characteristics

A technology of change detection and statistical characteristics, applied in the field of remote sensing image processing, can solve the problems of underfitting of difference image probability distribution and insufficient information utilization, etc., and achieve the effect of improving accuracy, improving efficiency, and enriching time-space information

Active Publication Date: 2020-07-17
WUHAN UNIV
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[0004] The purpose of the present invention is to fundamentally overcome the problems of insufficient information utilization and underfitting of the probability distribution of difference images in the unsupervised change detection of SAR images, and propose to use comprehensive test statistics and an improved minimum error threshold selection method to analyze time-series PolSAR images. Perform change detection

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  • Time sequence PolSAR image unsupervised change detection method considering statistical characteristics
  • Time sequence PolSAR image unsupervised change detection method considering statistical characteristics
  • Time sequence PolSAR image unsupervised change detection method considering statistical characteristics

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[0032] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0033] Step 1. Perform geometric and radiometric corrections on the PolSAR data in each time phase by using related software NEST, Envi, and PolSARpro; select the same reference image, and use the intensity cross-correlation method to perform a coarse-to-fine matching strategy on the time-series PolSAR data. Registration makes the registration accuracy reach the sub-pixel level; the registered PolSAR data is processed with refined Lee filtering to suppress the influence of coherent speckle noise on change detection to a certain extent. Assume that k represents the starting image position, and 0<k<n, cn represents the number of changes in the time series; let the initial value be k=1, cn=0.

[0034] Step 2, select the covariance matrix that can reflect the characteristics of PolSAR data and use X i Indicates that, considering ...

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Abstract

The invention provides a timing sequence full-polarization synthetic aperture radar image unsupervised change detection method considering statistical characteristics, and mainly solves the problems of insufficient polarization information utilization and underfitting of differential image probability statistical distribution in an existing method. According to the method, rich spatio-temporal information provided by long-time sequence PolSAR images is fully utilized, comprehensive test statistics and an improved minimum error threshold selection method are combined, and ground object change detection information of a research area is extracted. All parameters can be automatically acquired, the execution speed is high, rich space-time information of a time sequence PolSAR image can be fully utilized, and a change detection result is efficiently and accurately acquired. Meanwhile, the method is not only suitable for time sequence PolSAR image change detection, but also can be well applied to change detection of single-polarization and dual-polarization SAR data, and provides a basis for large-range and long-time change detection of an observation area.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and is a time-series image change detection algorithm, specifically a new method for time-series Polarimetric Synthetic Aperture Radar (Polarimetric Synthetic Aperture Radar, PolSAR) image change detection. Background technique [0002] In remote sensing image processing, change detection is a technical means to make multiple observations of the same location and quickly identify the change information of ground objects. SAR sensors are not affected by light and cloudy weather, and can detect changes in ground objects for a long time. The unsupervised change detection method has the characteristics of simple design and fast processing speed, and is widely used in the research of radar image change detection. The unsupervised change detection method mainly obtains the results of ground object change detection in the research area through preprocessing, difference image ext...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/35G06T7/136G06F17/18G06K9/62
CPCG06T7/35G06T7/136G06F17/18G06T2207/10044G06F18/22
Inventor 赵金奇常永雷牛玉芬李平湘杨杰陈奥赵伶俐
Owner WUHAN UNIV
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