基于数学形态学的高分遥感影像地震重点目标信息提取
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摘要
重点目标是抗震救援的关键,重点目标的破坏大多与目标本身的破坏或破坏前后的形态变化有关。本文利用数学形态学方法对地物形态特征(包括形状、大小、方向等)处理的优势和思路,构建了重点目标信息提取流程和算法,并利用海地地震的高分辨率遥感影像,对震后油罐破损状态的分离和提取、以及对机场跑道旧损状态的提取。试验结果表明,对于形态上能够明显区别于背景的重点目标,可以利用灰度和结构信息通过数学形态学进行提取。而且数学形态学算法构造灵活,处理速度快,便于硬件实现,对应急救援的快速处理有一定应用前景。
Earthquake key objects are densely populated areas and key facilities,which include schools,hospitals,dangerous goods,transportation hub and so on.They are the main goal of the emergency and rescue after earthquakes occurred.This paper makes full use of the processing advantages of morphological characteristics(including shape,size,direction,etc.) based on mathematical morphology,and constructs the extraction algorithm and process of the key object information.And then,the method has been tested using high resolution remote sensing image from the 2010 Haiti earthquake.Separation and extraction of the oil tank damage state is realized.In the same time,the airport runway old damage state is extracted.The test results show that key goals obviously differentiated from the background,gray scale and structure of information can be used for extraction through mathematical morphology.Test results also show that mathematical morphology algorithm has application prospect in the emergency rescue rapid processing.
Earthquake key objects are densely populated areas and key facilities,which include schools,hospitals,dangerous goods,transportation hub and so on.They are the main goal of the emergency and rescue after earthquakes occurred.This paper makes full use of the processing advantages of morphological characteristics(including shape,size,direction,etc.) based on mathematical morphology,and constructs the extraction algorithm and process of the key object information.And then,the method has been tested using high resolution remote sensing image from the 2010 Haiti earthquake.Separation and extraction of the oil tank damage state is realized.In the same time,the airport runway old damage state is extracted.The test results show that key goals obviously differentiated from the background,gray scale and structure of information can be used for extraction through mathematical morphology.Test results also show that mathematical morphology algorithm has application prospect in the emergency rescue rapid processing.
引文
[1]李亦纲.基于高分辨率遥感影像的震后重点搜救目标判定模型初步研究[J].地震学报,2011,33(4):532-538.
[2]王岩,王晓青,窦爱霞.面向对象遥感分类方法在汶川地震震害提取中的应用[J].地震,2009,29(3):54-60.
[3]窦爱霞,王晓青,丁香,等.遥感图像震害特征组合增强模型及其算法实现[J].震灾防御技术,2009,4(4):373-379.
[4]柳稼航,杨建峰,秦绪文.城市房屋震害的区域分析法与点特征判据算法的对比研究[J].自然灾害学报,2004,13(5):149-156.
[5]张景发,谢礼立,陶夏新.建筑物震害遥感图象的变化检测与震害评估[J].自然灾害学报,2002,11(2):59-64.
[6]明冬萍,骆剑承,沈占锋,等.高分辨率遥感影像信息提取与目标识别技术研究[J].测绘科学,2006,30(3):18-30.
[7]雷小奇,王卫星,赖均.一种基于形状特征进行高分辨率遥感影像道路提取方法[J].测绘学报,2009,38(5):457-464.
[8]Matheron G.Random Sets and Integral Geometry[M].NewYork:Wiley,1975.
[9]Serra J.Image Analysis and Mathematical Morphology[M].London:Academic Press,1982.
[10]Gonzalez C Rafael,Woods E Richard.数字图像处理(MATLAB版)[M].阮秋琦等译.北京:电子工业出版社,2005.276-283.
[11]刘生,王潇宇,邱新法,等.基于数学形态学的高空间分辨率遥感影像几何特征提取[J].地球信息科学,2008,10(2):251-256.
[12]杨述斌,彭复员,张增常.基于形态学的遥感图像全方位边缘检测算法研究[J].遥感信息,2003,(1):2-3.
[13]张果,李晓娟,张宪.基于迭代阈值和形态学的图像边缘检测[J].微计算机信息,2007,27(9):298-300.
[14]邓洁,查良松.基于HPF融合与数学形态学的ETM+遥感影像道路提取[J].石家庄学院学报,2012,14(3):96-101.
[15]吕书强,张思博.基于阈值分割和形态学的高分辨率遥感影像道路提取[J].北京建筑工程学院学报,2012,28(1):35-39.
[16]李利伟,刘吉平,尹作为.基于数学形态学的高分辨率遥感影像道路提取[J].遥感信息,2005,(5):9-15.
[17]汪洋,郑亲波,张钧屏.基于数学形态学的红外图像小目标检测[J].红外与激光工程,2003,33(1):28-31.
[18]张敏,杨武年,黄瑾,等.汶川地震区航空影像地质灾害自动识别技术[J].地理与地理信息科学,2008,24(6):42-46.
[19]曾繁如,何政伟,李苗.MATLAB软件与ALOS遥感影像在震害建筑物自动识别中的应用以都江堰市区为例[J].西北地震学报,2009,31(4):327-332.
[20]尹京苑,柳稼航,单新建,等.基于图像结构信息的城市房屋震害特征自动提取技术[J].遥感信息,2004,(1):27-30.
[21]柳稼航,单新建,尹京苑,等.遥感图象自动识别城市震害房屋以2001年印度库奇地震和1976年唐山地震为例[J].地震学报,2004,26(6):623-633.
[22]沙秀艳,何友.基于阈值分割的数学形态学道路标识线检测[J].鲁东大学学报(自然科学版),2007,23(1):28-30.
[23]崔屹.图像处理与分析数学形态学方法及应用[M].北京:科学出版社,2000.
[24]http:∥space.tv.cctv.com/act/article.jsp?articleId=ARTI1263408000413855&nowpage=4,2012.
[2]王岩,王晓青,窦爱霞.面向对象遥感分类方法在汶川地震震害提取中的应用[J].地震,2009,29(3):54-60.
[3]窦爱霞,王晓青,丁香,等.遥感图像震害特征组合增强模型及其算法实现[J].震灾防御技术,2009,4(4):373-379.
[4]柳稼航,杨建峰,秦绪文.城市房屋震害的区域分析法与点特征判据算法的对比研究[J].自然灾害学报,2004,13(5):149-156.
[5]张景发,谢礼立,陶夏新.建筑物震害遥感图象的变化检测与震害评估[J].自然灾害学报,2002,11(2):59-64.
[6]明冬萍,骆剑承,沈占锋,等.高分辨率遥感影像信息提取与目标识别技术研究[J].测绘科学,2006,30(3):18-30.
[7]雷小奇,王卫星,赖均.一种基于形状特征进行高分辨率遥感影像道路提取方法[J].测绘学报,2009,38(5):457-464.
[8]Matheron G.Random Sets and Integral Geometry[M].NewYork:Wiley,1975.
[9]Serra J.Image Analysis and Mathematical Morphology[M].London:Academic Press,1982.
[10]Gonzalez C Rafael,Woods E Richard.数字图像处理(MATLAB版)[M].阮秋琦等译.北京:电子工业出版社,2005.276-283.
[11]刘生,王潇宇,邱新法,等.基于数学形态学的高空间分辨率遥感影像几何特征提取[J].地球信息科学,2008,10(2):251-256.
[12]杨述斌,彭复员,张增常.基于形态学的遥感图像全方位边缘检测算法研究[J].遥感信息,2003,(1):2-3.
[13]张果,李晓娟,张宪.基于迭代阈值和形态学的图像边缘检测[J].微计算机信息,2007,27(9):298-300.
[14]邓洁,查良松.基于HPF融合与数学形态学的ETM+遥感影像道路提取[J].石家庄学院学报,2012,14(3):96-101.
[15]吕书强,张思博.基于阈值分割和形态学的高分辨率遥感影像道路提取[J].北京建筑工程学院学报,2012,28(1):35-39.
[16]李利伟,刘吉平,尹作为.基于数学形态学的高分辨率遥感影像道路提取[J].遥感信息,2005,(5):9-15.
[17]汪洋,郑亲波,张钧屏.基于数学形态学的红外图像小目标检测[J].红外与激光工程,2003,33(1):28-31.
[18]张敏,杨武年,黄瑾,等.汶川地震区航空影像地质灾害自动识别技术[J].地理与地理信息科学,2008,24(6):42-46.
[19]曾繁如,何政伟,李苗.MATLAB软件与ALOS遥感影像在震害建筑物自动识别中的应用以都江堰市区为例[J].西北地震学报,2009,31(4):327-332.
[20]尹京苑,柳稼航,单新建,等.基于图像结构信息的城市房屋震害特征自动提取技术[J].遥感信息,2004,(1):27-30.
[21]柳稼航,单新建,尹京苑,等.遥感图象自动识别城市震害房屋以2001年印度库奇地震和1976年唐山地震为例[J].地震学报,2004,26(6):623-633.
[22]沙秀艳,何友.基于阈值分割的数学形态学道路标识线检测[J].鲁东大学学报(自然科学版),2007,23(1):28-30.
[23]崔屹.图像处理与分析数学形态学方法及应用[M].北京:科学出版社,2000.
[24]http:∥space.tv.cctv.com/act/article.jsp?articleId=ARTI1263408000413855&nowpage=4,2012.
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