一種基于概率圖模型的多時(shí)相SAR相干變化檢測方法

冀廣宇; 董勇偉; 李焱磊; 梁興東

doi:10.11999/JEIT170208

一種基于概率圖模型的多時(shí)相SAR相干變化檢測方法

doi: 10.11999/JEIT170208

2.
(中國科學(xué)院電子學(xué)研究所微波成像技術(shù)重點(diǎn)實(shí)驗(yàn)室北京 100190) ②(中國科學(xué)院大學(xué) 北京 100049)

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出版歷程
- 收稿日期: 2017-03-07
- 修回日期: 2017-05-24
- 刊出日期: 2017-12-19

A Multi-temporal SAR Coherent Change Detection Method Based on Probabilistic Graphical Models

2.
(Key Laboratory of Science and Technology on Microwave Imaging, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China)

摘要

摘要: 相干變化檢測(CCD)利用重軌SAR數(shù)據(jù)對(duì)場景中表現(xiàn)為低相干特性的變化區(qū)域具有良好的檢測性能，然而場景中諸如植被、陰影、強(qiáng)散射旁瓣、低散射等區(qū)域也呈現(xiàn)低相干特性，對(duì)檢測結(jié)果造成干擾，尤其在高波段SAR CCD中，對(duì)檢測效果影響更加明顯。該文利用多時(shí)相SAR數(shù)據(jù)形成的相干變化差異圖像(CCD圖像)建立概率圖模型，提出一種多時(shí)相CCD處理方法。該方法以多時(shí)相CCD圖像作為觀測量，通過選取合適的參與處理圖像數(shù)量及優(yōu)化場景中變化區(qū)域的分類，計(jì)算目標(biāo)變化區(qū)域的后驗(yàn)概率，可有效減小低相干干擾區(qū)域造成的影響。仿真和實(shí)測數(shù)據(jù)結(jié)果驗(yàn)證了該方法的正確性和有效性。
- 重軌合成孔徑雷達(dá) /
- 相干變化檢測 /
- 多時(shí)相 /
- 概率圖模型 /
- 后驗(yàn)概率
Abstract: Coherent Change Detection (CCD) has good performance on detecting change regions with low coherence in the scene by using repeat-pass Synthetic Aperture Radar (SAR) data. However, some regions as vegetation, radar shadows, sidelobes of strong reflectivity and low reflectivity areas show low coherent character as well, which disturbs the result of change detection, especially in high frequency band SAR CCD with more evident disturbance. This paper proposes a multi-temporal CCD method by establishing a probabilistic graphical model using CCD images formed by multi-temporal SAR data. In this method, multi-temporal CCD images are used as observations to calculate a posterior probability of objective change region via choosing appropriate number of processing CCD images and optimizing the classification of change regions in the scene. The proposed method can reduce the disturbance of low coherence disturb regions effectively. The simulated and experimental results demonstrate the validity and effectiveness of the proposed method.
- Repeat-pass SAR /
- Coherent Change Detection (CCD) /
- Multi-temporal /
- Probabilistic graphical models /
- Posterior probability

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