基于多尺度马尔科夫随机场融合的遥感图像变化检测  

Remote Sensing Image Variation Detection on Multi-scale MRF Fusion

作　　者：陈忠辉[1] 王卫星[1] 于天超[2] 林丽群[1] 

机构地区：[1]福州大学物理与信息工程学院,福建福州350108 [2]中国飞行试验研究院,陕西西安710089

出　　处：《四川大学学报（工程科学版）》2011年第3期104-108,共5页Journal of Sichuan University (Engineering Science Edition)

基　　金：国家自然科学基金资助项目(60873186);教育部科学技术研究重点项目(210184);重庆市教委科学技术研究资助项目(KJ100525)

摘　　要：在区域变化检测中,为了克服配准误差或噪声引起的伪变化,从多尺度融合的角度出发,对多尺度分析应用于遥感图像变化检测进行了探讨。首先利用小波变换对原始图像进行多尺度分解,然后利用马氏距离判决函数对不同尺度图像进行变化检测,最后利用马尔科夫随机场将不同尺度变化检测结果进行融合。由于马尔科夫随机场融合方法充分考虑了相邻像素间的相关性和不同尺度检测结果的联系,从而使融合结果更细致和精确。一系列图像的实验结果证明本方法具有很好的实用性和鲁棒性。In order to increase image registration accuracy in change detection,from the view of multi-scale fusion,a method was proposed for region variation detection,which applied the multi-scale analysis to remote sensing image.First of all,Wavelet transform was adopted to decompose original images,then Mahalanobis distance decision function was used to detect the changes of different scale images,and finally Markov random field was applied to fuse different scale change detection results.Since Markov random field fusion method took full account of the correlation between the adjacent pixels and the links of different scale change detection results,the fusion results were more accurate and practical.The testing results showed that this method is effective and robust.

关 键 词：变化检测 多尺度 马氏距离 马尔科夫随机场 图像融合 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]