有监督上下文相似度图像变化检测

图像变化检测中存在变化区域过高估计的问题. 为解决此问题，提出一种基于上下文相似度的有监督图像变化检测方法，用于二时刻高分辨率多光谱卫星图像的变化检测. 利用上下文相关度和像素点相邻部分的局部斜率和截距来描述变化方向，然后通过带有局部斜率和截距的支持向量机（SVM）进行图像变化检测. 数值实验得出了用于高分辨率地震（包括建筑损毁）二元多光谱图像的变化检测的结果. 与已有方法相比，明显抑制了错分类现象，对于解决变化区域过高估计问题是有效的.

Image Change Detection with Supervised Context Similarity

To deal with the problem that changed areas are overestimated in image change detection, a context-sensitive similarity based supervised image change detection method is proposed and applied in bi-temporal high resolution and multispectral satellite image change detection. It exploits both context-sensitive magnitude and direction of change in the vicinity of each pixel by means of local intercept and slope, and uses support vector machine (SVM) with local intercept and slope for image change detection. The results are from experiments for change detection of high resolution bi-temporal multispectral earthquake images including building damage. It is obvious that the false alarms are mostly reduced, which means it is effective for solving changed area overestimation problems.