| 一种运用纹理和光谱特征消除投影差影响的建筑物变化检测方法 |
| |
| 引用本文： | 袁修孝, 宋妍. 一种运用纹理和光谱特征消除投影差影响的建筑物变化检测方法[J]. 武汉大学学报 ( 信息科学版), 2007, 32(6): 489-493. |
| |
| 作者姓名： | 袁修孝 宋妍 |
| |
| 作者单位： | 1 武汉大学遥感信息工程学院,武汉市珞喻路129号,4300792 武汉大学测绘遥感信息工程国家重点实验室,武汉市珞喻路129号,430079 |
| |
| 基金项目： | 国家重点基础研究发展计划(973计划);教育部全国优秀博士学位论文作者专项基金;教育部长江学者和创新团队发展计划创新团队资助项目 |
| |
| 摘 要： | 针对不同时期高分辨率遥感影像变化检测中城区建筑物因投影差差异所产生的误检测现象,提出了一种综合应用光谱和纹理特征的建筑物变化检测方法。以变化和未发生变化地物影像的散度作为可分性依据,首先对光谱差分影像在混合高斯密度模型下建模,并采用马尔可夫最小错误概率准则提取初始变化区域,往往含有错判的建筑物。然后将误判建筑物影像类和真实变化影像类构成训练集,通过引入多通道Gabor滤波器,提取训练集的纹理差分特征,并采用分类别PCA变换实施纹理差分特征的选择。最后对选择出的纹理差分特征依据高斯混合密度模型建模,并用马尔可夫最小错误概率提取真变化区域,即可去除光谱信息检测所产生的伪变化。试验表明,本文方法能够较好地解决建筑物变化的错判问题,提高了影像变化检测的精度。
|
| 关 键 词： | 影像变化检测 多通道Gabor滤波器 分类别PCA变换 混合高斯密度模型 马尔可夫最小错误概率 |
| 文章编号： | 1671-8860（2007）06-0489-05 |
| 收稿时间： | 2007-03-06 |
| 修稿时间： | 2007-03-06 |
A Building Change Detection Method Considering Projection Influence Based on Spectral Feature and Texture Feature |
| |
| YUAN Xiuxiao, SONG Yan. A Building Change Detection Method Considering Projection Influence Based on Spectral Feature and Texture Feature[J]. Geomatics and Information Science of Wuhan University, 2007, 32(6): 489-493. |
| |
| Authors: | YUAN Xiuxiao SONG Yan |
| |
| Affiliation: | 1 School of Remote Sensing and Information Engineering,Wuhan University,129 Luoyu Road,Wuhan 430079,China2 State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University, 129 Luoyu Road,Wuhan 430079,China |
| |
| Abstract: | A change detection method for high-resolution remotely sensed imagery is designed by combined the texture features with spectral features.The method can decrease change detection errors caused by building projection difference between two period imageries.It utilizes transform divergence between change and no-change to establish change detection strategy.Firstly,the differential spectral features are modeled by using Gaussian mixture model(GMM) and initial change area is obtained by using MRF minimum error probability.But for high-resolution imagery,the projection difference will disturb change area's result.For decreasing these errors,the texture features are extracted by multi-channel Gabor filter.When using these texture features,it is necessary to reduce these texture features' correlation and relieve computation burden.A class-within PCA is adopted to select texture features.Using selected texture features,the initial change area is modeled by using GMM and "false change" is got rid of using MRF minimum error probability.The experiment has shows that the mentioned method can remove false change caused by projection difference and improve change detection accuracy. |
| |
| Keywords: | remote sensing imagery change detection multi-channel Gabor filter divergence of class-within PCA Gaussian mixture model Markov random field minimum error probability |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《武汉大学学报(信息科学版)》浏览原始摘要信息 |
|
点击此处可从《武汉大学学报(信息科学版)》下载全文 |
