基于遥感影像的重要地物的变化检测和标注

破坏性灾害会造成巨大危害和损失，灾后一定时间内由于信息匮乏，使得对了解灾情和救灾都极为不利。为了及时获取灾区建筑物、道路、桥梁、水库等重要地物的倒塌和毁坏信息，本文给出了一种可自动识别和标注灾害前后遥感图像差异区域的方法。首先对时序遥感影像通过BM3D方法去除高斯噪声，然后利用SIFT方法进行图像配准，通过对差分图像采用Wv_Canny边缘检测方法获得差异区域重要地物的边缘信息，最后识别并标注出发生变化的重要地物，真实遥感图像实验结果按建筑物变化面积比较，正确率78~79%，误检率21~22%，无漏检率。仿真试验和实际遥感影像处理表明：本文方法可有效识别和标注建筑物等重要地物的差异区，有利于灾后破坏性地物的及时了解和救助工作。

Change detection and annotation of important ground objects based on remote sensing images

The destructive disaster will cause heavy damage and loss. That the lack of information in a certain period of time after the disaster makes it extremely disadvantageous to understand the disaster situation and to provide disaster relief. In order to obtain timely collapse and damage information of buildings, roads, bridges, reservoirs and other important ground objects in disaster areas, this paper presents a method which can automatically identifies and labels the difference regions of remote sensing images before and after disasters.Firstly, the Gaussian noise is removed from the temporal remote sensing images by the BM3D method, and then the SIFT method is used for image registration. The edge information of important ground objects in different areas is obtained by using Wv_Canny edge detection method for difference images. Finally, the important ground objects that have changed are identified and annotated.The experimental results of remote sensing image are compared according to the change area of the building, the correct rate is 78~79%, the false detection rate is 21~22%, and there is no missed detection rate.Simulation experiment and actual remote sensing image processing show that the proposed method can effectively identify and mark the difference areas of important ground objects such as buildings, which is conducive to timely understanding and rescue of destructive ground objects after disaster.