基于ICA/MNF变换的高分影像滑坡灾害检测方法研究
详细信息 本馆镜像全文    |  推荐本文 | | 获取馆网全文
摘要
快速准确地从灾后影像中提取出受灾区域对于灾后救援具有重要意义。鉴于现有提取方法过度依赖滑坡在影像中的光学、纹理等特征的问题,研究了一种结合独立成分分析(ICA)与最小噪声比率变换(MNF)的变化检测方法,以单一时相的影像为基础,运用基于负熵最大化的Fast-ICA算法分离出两个时相影像相互正交的独立成分,并构建对应独立成分的差异影像,最后用最小噪声比率变换实现分布于各个差异影像上变化信息的集中,应用直方图阈值法得到了最终的滑坡灾害信息。选取了滑坡灾害前后两时相的高分辨率遥感影像数据进行实验,结果证实了方法的可行性。
It is very important for disaster relief to extract disaster information from the disaster images quickly and accurately. Given the existing methods depends on landslide disasters' texture and other information on images heavily,a new method is studied which combined the independent component analysis and the Minimum Noise Fraction Transformation. It based on the single image,separated the independent component image using the FastICA algorithm of maximum neg-entropy approximations and built the components' difference images,focused the different singles which distributed all of difference images based on the MNF and got the change information by the threshold from histogram method finally. Experiment results demonstrated the method's utility with images both before and after the disaster.
引文
[1]宫鹏,黎夏,徐冰.高分辨率影像解译理论与应用方法中的一些研究问题[J].遥感学报,2006,10(1):1-5.
    [2]李松,李亦秋,安裕伦.基于变化检测的滑坡灾害自动识别[J].遥感信息,2010(1):27-31.
    [3]赵祥,李长春,苏娜.滑坡泥石流的多源遥感提取方法[J].自然灾害学报,2008,18(6):29-32.
    [4]陈莹,孙洪泉,赵祥,等.地震灾区河谷滑坡检测的遥感分析——以北川县滑坡为例[J].自然灾害学报,2011,20(1):97-104.
    [5]鲁学军,史振春,尚伟涛,等.滑坡高分辨率遥感多维解译方法及其应用[J].中国国象图形学报,2014,19(1):141-149.
    [6]贾春阳,李卫华,李小春,等.基于ICA的变化检测新方法[J].光电工程,2013,40(12):39-43.
    [7]武辰,杜博,张良培.基于独立成分分析的高光谱变化检测[J].遥感学报,2012,16(3):545-561.
    [8]申丽岩,方滨,沈毅.基于负熵极大的独立分量分析方法[J].中北大学学报,2005,26(6):396-399.
    [9]钟家强,王润生.基于独立成分分析的多时相遥感图像变化检测[J].电子与信息学报,2006,28(6):994-998.
    [10]史习智.盲信息处理[M].上海:上海交通大学出版社,2008:56-62.
    [11]Bingham E,Hyvarinen A.A fast fixed-point algorithm for independent component analysis of complex-valued signals[J].Neural Systems,2000,10(1):1-8.
    [12]Zhang Lu,Wang Yan,Liao Mingsheng,et al.SMNF-based spatial fuzzy clustering of remote sensing imagery[C]//Proceeding of SPIE Third International Symposium on Multispectral Image Proceeding and Pattern Recognition,Beijing,China,2003:632-635.
    [13]Nielsen AA.Kernel maximum autocorrelation factor and minimum noise fraction transformations[J].IEEE Transactions on Image Processing,2011,20(3):612-624.
    [14]张路.基于多元统计分析的遥感影像变化检测方法研究[D].武汉:武汉大学,2004:56-74.

版权所有:© 2023 中国地质图书馆 中国地质调查局地学文献中心