基于特征分析的遥感影像变化检测方法研究
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摘要
图像变化检测技术旨在检测同一地区不同时相的变化情况。这一技术在民用与军事等方面都有着非常广泛的应用,其多年的理论研究和具体实践也己产生了大量的算法。当前基于遥感影像的变化检测算法很多是以像元为基础进行研究,而从纹理和形状等模式来综合研究相对较少。本文从目标图像特征分析着手进行遥感影像的变化检测技术研究与探讨,工作之一是利用小波理论进行图像纹理特征分析,然后进行变化检测;工作之二是利用目标的不变特征进行形状分析与提取,进而应用于变化分析。本文的主要工作和创新点如下:
1)阐述了变化检测研究背景和现状,指明了当前存在的主要问题,明确了本文的研究范围和基本思路。
2)概述出变化检测的一般流程,对用于变化检测的数据源以及图像预处理,如几何校正、辐射校正等关键技术进行了分析,并根据应用对象,即面状、线状及独立目标,对目前算法作了简要归类,详细阐述了各类算法中较经典的一些算法。
3)研究并实现了基于纹理特征的小波变化检测方法。该方法引入了小波理论,对其低频和高频系数采取不同的纹理特征提取方法,与传统方法相比具有更好的检测效果,比直接提取纹理特征又具有更快的速度,提高了检测效果与效率。
4)以传统迭代算法所获得的阈值为基础,增加一适当的常量,使其更适合于分割目标在影像中占有比例较小而且灰度较亮的情况,通过与其他方法比较得出其具有算法简单、分割效果更好的结论。
5)针对目标形状特征设计并实现了基于多不变特征的目标提取及变化检测方法。该方法主要针对独立目标(如人造小面元目标),实验表明其检测精度高且可实现各自影像变化目标的定位分析。
The technology of change detection based on remotely sensed images means that given the remotely sensed multi-temporal images, panchromatic or multi-spectral, one's aim is to detect the changes of ground feature or target by means of image processing and analyzing. This technology plays an important role in the field of civil and military affairs, and a large volume of algorithms have been put forward. Most of these algorithms were studied based on pixels, while only a few are synthetically studied from other patterns of image such as texture and shape. The aim of this paper is to realize the change detection of ground feature or target in remotely sensed images by image feature analysis. On the one hand, using image texture feature analysis by wavelet transformation is to detect change of images; on the other hand, using feature invariant of target image is to analyze the shape of targets, then extract targets and detect those changes. Main works of this paper are as follows:
1) It analyzes the background and current status of change detection, points out the main problems of the existing algorithms, brings forward the range and basic ideas of this paper.
2) Aiming to common process of change detection based on remotely sensed multi-temporal images, it introduces the data source and the work of image preprocessing in favor of change detection, such as geometric correction and radiometric correction. And according to the applied objects, it summarizes the existing algorithms, detailed expounded some classical methods.
3) It studies an algorithm of change detection based on texture feature by wavelet. This method applies wavelet theory to extract different features from wavelet approximate constituent and detail constituents. Compared to conventional methods, this method has better effect, and has faster speed than directly extracting texture feature. So it improves change detection effect and efficiency.
4) The segmentation algorithm of iterative threshold is developed, which is rather suitable to segment targets with small proportion of the image. And compared to other existing methods, this method is simple and has better effect of segmentation.
5) This paper also puts forward a method of target extraction and its change detection based on multi-invariant features. It mainly aims at the isolated target, realizing the quantitative and positional analysis with fine accuracy for mutative targets.
1)阐述了变化检测研究背景和现状,指明了当前存在的主要问题,明确了本文的研究范围和基本思路。
2)概述出变化检测的一般流程,对用于变化检测的数据源以及图像预处理,如几何校正、辐射校正等关键技术进行了分析,并根据应用对象,即面状、线状及独立目标,对目前算法作了简要归类,详细阐述了各类算法中较经典的一些算法。
3)研究并实现了基于纹理特征的小波变化检测方法。该方法引入了小波理论,对其低频和高频系数采取不同的纹理特征提取方法,与传统方法相比具有更好的检测效果,比直接提取纹理特征又具有更快的速度,提高了检测效果与效率。
4)以传统迭代算法所获得的阈值为基础,增加一适当的常量,使其更适合于分割目标在影像中占有比例较小而且灰度较亮的情况,通过与其他方法比较得出其具有算法简单、分割效果更好的结论。
5)针对目标形状特征设计并实现了基于多不变特征的目标提取及变化检测方法。该方法主要针对独立目标(如人造小面元目标),实验表明其检测精度高且可实现各自影像变化目标的定位分析。
The technology of change detection based on remotely sensed images means that given the remotely sensed multi-temporal images, panchromatic or multi-spectral, one's aim is to detect the changes of ground feature or target by means of image processing and analyzing. This technology plays an important role in the field of civil and military affairs, and a large volume of algorithms have been put forward. Most of these algorithms were studied based on pixels, while only a few are synthetically studied from other patterns of image such as texture and shape. The aim of this paper is to realize the change detection of ground feature or target in remotely sensed images by image feature analysis. On the one hand, using image texture feature analysis by wavelet transformation is to detect change of images; on the other hand, using feature invariant of target image is to analyze the shape of targets, then extract targets and detect those changes. Main works of this paper are as follows:
1) It analyzes the background and current status of change detection, points out the main problems of the existing algorithms, brings forward the range and basic ideas of this paper.
2) Aiming to common process of change detection based on remotely sensed multi-temporal images, it introduces the data source and the work of image preprocessing in favor of change detection, such as geometric correction and radiometric correction. And according to the applied objects, it summarizes the existing algorithms, detailed expounded some classical methods.
3) It studies an algorithm of change detection based on texture feature by wavelet. This method applies wavelet theory to extract different features from wavelet approximate constituent and detail constituents. Compared to conventional methods, this method has better effect, and has faster speed than directly extracting texture feature. So it improves change detection effect and efficiency.
4) The segmentation algorithm of iterative threshold is developed, which is rather suitable to segment targets with small proportion of the image. And compared to other existing methods, this method is simple and has better effect of segmentation.
5) This paper also puts forward a method of target extraction and its change detection based on multi-invariant features. It mainly aims at the isolated target, realizing the quantitative and positional analysis with fine accuracy for mutative targets.
引文
[1]赵英时等.遥感应用分析原理与方法[M].北京:科学出版社,2003.
[2]顾文俊,赵忠明.基于变化检测技术的城区建筑变化目标提取[J].计算机工程与应用,2004,(1),198-200.
[3]阎福礼,李震,邵芸等.基于NOAA/AVHRR数据的西部植被覆盖变化检测[J].兰州大学学报(自然科学版),2003,39(2),90-94.
[4]李全,李霖等.基于Landsat TM影像的城市变化检测研究[J].武汉大学学报·信息科学版,2005,30(4),351-353.
[5]顾文俊.变化检测方法在城市规划中的应用[D].北京中国科学院研究生院硕士学位论文,2003.
[6]方圣辉,佃袁勇等.基于边缘特征的变化检测方法研究[J].武汉大学学报·信息科学版2005,30(2),135-138
[7]姜涛,马国锐等.基于遥感影像的变化检测技术[J].计算机应用研究,2005,(2),255-257.
[8]窦爱霞.震害遥感图像变化检测技术研究[D].山东科技大学硕士学位论文,2003.
[9]Brian Pilemann Olsen.Automatic Change Detection for Validation of Digital Map databases.XXth ISPRS Congress,July 2004 Istanbul,Turkey.
[10]李德仁.利用遥感影像进行变化检测[J].武汉大学学报·信息科学版,2003,28(特刊),7-12.
[11]陈志鹏.基于纹理特征的差值变化检测方法研究.[D].中国科学院研究生院硕士学位论文,2002..
[12]Christopher Munyati.Use of Principal Component Analysis(PCA)of Remote Sensing Images in Wetland Change Detection on the Kafue Flats.Zambia.Geocarto Intemational[J],2004,19(3),13-22.
[13]Donna Haverkamp,Rick Poulsen.Change Detection Using IKONOS Imager).XXth ISPRS Congress[C].Istanbul,Turkey.2004.
[14]李小春,陈鲸.一种变化检测的新算法[J].宇航学报,2005,26(3),334-338.
[15]Jin Chen,Peng Gong.Land-Use/Land-Cover Change Detection Using Improved Change-Vector Analysis[J].Photogrammetric Engineering & Remote Sensing,April,2003,69(4),369-379.
[16]Leena Matikainen,Juha Hyyppa,Harti Kaartinen.Automatic Detection of Changes From Laser Scanner and Aerial Image Date For Updating Building Maps.XXth ISPRS Congress[C],Istanbul,Turke,2004.
[17]Brian PiIemann Olsen.Automatic Change Detection for VaIidation of Digital Map databases.XXth ISPRS Congress[C],Istanbul,Turkey,2004.
[18]F.Samadzadegan.Automatic Change Detection of Geospatial Databases Based on A Decision-1evel Fusion Technique[C].XXth ISPRS Congress,Istanbul,Turkey,2004.
[19]刘直芳,张剑清.城区变化检测的一种方法[J].测绘通报,2001(2),1-2.
[20]阎福礼,李震等.基于NOAA/AVHRR数据的西部植被覆盖变化检测[J].兰州大学学报(自然科学版)2003.39(2),90-94.
[21]Andteas Niedermeier,Susanne Lehner,Joost van der Sanden.Monitoring Big River Estuaries Using SAR Images.
[22]张朝阳.遥感影像海岸线提取及其变化检测技术研究[D].解放军信息工程大学硕士学位论文,2006.
[23]Pierfrancesco Lombardo,Tiziana Macri Pellizzeri.Maximum Likelihood Signal Processing Techniques to Detect A Step Pattern of Change in Multitemporal SAR Images.IEEE,2002.
[24]蔡纯,孙洪等.基于区域似然比的SAR图像变化检测[J].武汉大学学报(理学版)2005 51(1)109-113.
[25]陈雪,戴芹等.多光谱遥感数据直接分类变化检测的神经网络方法研究[J].计算机工程与应用,2004.(28),12-15.
[26]张永生,王仁礼.遥感动态检测[M].北京:解放军出版社,1999.
[27]朱述龙,朱宝山等.遥感图像处理与应用[M].北京:科学出版社,2006.
[28]X.Dai and S.Khorram.The Effects of Image Misregistration On The Accuracy of Remotely Sensed Change Detection.IEEE Trans.Geosci.Remote Sens.,1998.
[29]阮秋琦.数字图像处理学[M].北京:电子工业出版社,2001.
[30]郝文化.MATLAB图形图象处理应用教程[M].北京:中国水利水电出版社,2004.
[31]Rafael C.Gonzalez,Richard E.Woods,Steven L.Eddins.Digital Image Processing Using MATLAB[M].BEIJING:Publishing House of Electronics Industry,2004.
[32]张祖勋,张剑清.数字摄影测量学[M].武汉:武汉测绘科技大学出版社.,1996.
[33]冯德俊.基于遥感的土地利用变化监测及其信息自动提取[D].西南交通大学博士学位论文,2004.
[34]沈帮乐.计算机图像处理[M].北京:解放军出版社,1995.
[35]刘德刚.基于多时相遥感影像的变化检测与分析[D]解放军信息工程大学硕士学位论文,2005.
[36]陈杉,秦其明.基于小波变换的高分辨率影像纹理结构分类方法[J].地理与地理信息科学,2003,19(3):6-10.
[37]张永生,戴晨光等.天基多源遥感信息融合-理论、算法与应用系统[M].北京:科学出版社.2005.
[38]林卉,杜培军等.一种基于小波变换的边缘检测方法[J].测绘工程,2005,14(2),15-17.
[39]耿则勋.小波变换理论及在遥感影像压缩中的应用[M].北京:测绘出版社,2002.
[40]P.Rosin.Thresholding for Chang Detection.CoMput.Vis.Image Understanding,Vol.86,no.2,2002.
[41]P.Rosin and E.Ioannidis.Evaluation of Global Image Thresholding for Change Detection.,Pattern recognit.Lett.,Vol.24 no.14.2003.
[42]张天序.成像自动目标识别[M].湖北:湖北科学技术出版社,2005.
[43]严柏军,郑链等.基于不变矩特征匹配的快速目标检测算法[J].红外技术,2001.23(6),8-11.
[44]杨小冈,付光远.基于图像NMI特征的目标识别新方法[J].计算机工程,2002,28(6),149-151.
[45]张伟,吴刚等.基于不变矩特征匹配的目标定位方法的实现.光学技术,2005,31(3),441-445.
[46]余旭初.模式识别与图像分类[M].北京:解放军出版社,2000.
[47]Richard J.Radke,Srinivas Andra.,2005.Image Change Detection Algorithms:A Systematic Survey.IEEE.
[2]顾文俊,赵忠明.基于变化检测技术的城区建筑变化目标提取[J].计算机工程与应用,2004,(1),198-200.
[3]阎福礼,李震,邵芸等.基于NOAA/AVHRR数据的西部植被覆盖变化检测[J].兰州大学学报(自然科学版),2003,39(2),90-94.
[4]李全,李霖等.基于Landsat TM影像的城市变化检测研究[J].武汉大学学报·信息科学版,2005,30(4),351-353.
[5]顾文俊.变化检测方法在城市规划中的应用[D].北京中国科学院研究生院硕士学位论文,2003.
[6]方圣辉,佃袁勇等.基于边缘特征的变化检测方法研究[J].武汉大学学报·信息科学版2005,30(2),135-138
[7]姜涛,马国锐等.基于遥感影像的变化检测技术[J].计算机应用研究,2005,(2),255-257.
[8]窦爱霞.震害遥感图像变化检测技术研究[D].山东科技大学硕士学位论文,2003.
[9]Brian Pilemann Olsen.Automatic Change Detection for Validation of Digital Map databases.XXth ISPRS Congress,July 2004 Istanbul,Turkey.
[10]李德仁.利用遥感影像进行变化检测[J].武汉大学学报·信息科学版,2003,28(特刊),7-12.
[11]陈志鹏.基于纹理特征的差值变化检测方法研究.[D].中国科学院研究生院硕士学位论文,2002..
[12]Christopher Munyati.Use of Principal Component Analysis(PCA)of Remote Sensing Images in Wetland Change Detection on the Kafue Flats.Zambia.Geocarto Intemational[J],2004,19(3),13-22.
[13]Donna Haverkamp,Rick Poulsen.Change Detection Using IKONOS Imager).XXth ISPRS Congress[C].Istanbul,Turkey.2004.
[14]李小春,陈鲸.一种变化检测的新算法[J].宇航学报,2005,26(3),334-338.
[15]Jin Chen,Peng Gong.Land-Use/Land-Cover Change Detection Using Improved Change-Vector Analysis[J].Photogrammetric Engineering & Remote Sensing,April,2003,69(4),369-379.
[16]Leena Matikainen,Juha Hyyppa,Harti Kaartinen.Automatic Detection of Changes From Laser Scanner and Aerial Image Date For Updating Building Maps.XXth ISPRS Congress[C],Istanbul,Turke,2004.
[17]Brian PiIemann Olsen.Automatic Change Detection for VaIidation of Digital Map databases.XXth ISPRS Congress[C],Istanbul,Turkey,2004.
[18]F.Samadzadegan.Automatic Change Detection of Geospatial Databases Based on A Decision-1evel Fusion Technique[C].XXth ISPRS Congress,Istanbul,Turkey,2004.
[19]刘直芳,张剑清.城区变化检测的一种方法[J].测绘通报,2001(2),1-2.
[20]阎福礼,李震等.基于NOAA/AVHRR数据的西部植被覆盖变化检测[J].兰州大学学报(自然科学版)2003.39(2),90-94.
[21]Andteas Niedermeier,Susanne Lehner,Joost van der Sanden.Monitoring Big River Estuaries Using SAR Images.
[22]张朝阳.遥感影像海岸线提取及其变化检测技术研究[D].解放军信息工程大学硕士学位论文,2006.
[23]Pierfrancesco Lombardo,Tiziana Macri Pellizzeri.Maximum Likelihood Signal Processing Techniques to Detect A Step Pattern of Change in Multitemporal SAR Images.IEEE,2002.
[24]蔡纯,孙洪等.基于区域似然比的SAR图像变化检测[J].武汉大学学报(理学版)2005 51(1)109-113.
[25]陈雪,戴芹等.多光谱遥感数据直接分类变化检测的神经网络方法研究[J].计算机工程与应用,2004.(28),12-15.
[26]张永生,王仁礼.遥感动态检测[M].北京:解放军出版社,1999.
[27]朱述龙,朱宝山等.遥感图像处理与应用[M].北京:科学出版社,2006.
[28]X.Dai and S.Khorram.The Effects of Image Misregistration On The Accuracy of Remotely Sensed Change Detection.IEEE Trans.Geosci.Remote Sens.,1998.
[29]阮秋琦.数字图像处理学[M].北京:电子工业出版社,2001.
[30]郝文化.MATLAB图形图象处理应用教程[M].北京:中国水利水电出版社,2004.
[31]Rafael C.Gonzalez,Richard E.Woods,Steven L.Eddins.Digital Image Processing Using MATLAB[M].BEIJING:Publishing House of Electronics Industry,2004.
[32]张祖勋,张剑清.数字摄影测量学[M].武汉:武汉测绘科技大学出版社.,1996.
[33]冯德俊.基于遥感的土地利用变化监测及其信息自动提取[D].西南交通大学博士学位论文,2004.
[34]沈帮乐.计算机图像处理[M].北京:解放军出版社,1995.
[35]刘德刚.基于多时相遥感影像的变化检测与分析[D]解放军信息工程大学硕士学位论文,2005.
[36]陈杉,秦其明.基于小波变换的高分辨率影像纹理结构分类方法[J].地理与地理信息科学,2003,19(3):6-10.
[37]张永生,戴晨光等.天基多源遥感信息融合-理论、算法与应用系统[M].北京:科学出版社.2005.
[38]林卉,杜培军等.一种基于小波变换的边缘检测方法[J].测绘工程,2005,14(2),15-17.
[39]耿则勋.小波变换理论及在遥感影像压缩中的应用[M].北京:测绘出版社,2002.
[40]P.Rosin.Thresholding for Chang Detection.CoMput.Vis.Image Understanding,Vol.86,no.2,2002.
[41]P.Rosin and E.Ioannidis.Evaluation of Global Image Thresholding for Change Detection.,Pattern recognit.Lett.,Vol.24 no.14.2003.
[42]张天序.成像自动目标识别[M].湖北:湖北科学技术出版社,2005.
[43]严柏军,郑链等.基于不变矩特征匹配的快速目标检测算法[J].红外技术,2001.23(6),8-11.
[44]杨小冈,付光远.基于图像NMI特征的目标识别新方法[J].计算机工程,2002,28(6),149-151.
[45]张伟,吴刚等.基于不变矩特征匹配的目标定位方法的实现.光学技术,2005,31(3),441-445.
[46]余旭初.模式识别与图像分类[M].北京:解放军出版社,2000.
[47]Richard J.Radke,Srinivas Andra.,2005.Image Change Detection Algorithms:A Systematic Survey.IEEE.