中文摘要：

传统的像素级变化检测方法的检测性能受到以下凼素的严重制约：图像辐射差异、配准误差和差异图像分类门限的选取，并且难以从检测信息中提取出关键的变化．本文针对遥感图像中人造目标的变化检测问题，提出了一种综合特征级和像素级的两步变化检测算法．首先将大幅多时相遥感图像分成一系列子图像对，采用有监督子图像对分类方法，提取人造目标变化的感兴趣区域，然后采用像素级变化检测算法对感兴趣区域进行变化检测，得到定量的检测结果．实验结果表明了该算法的可行性和有效性．

英文摘要：

The detection accuracy of traditional pixel-level change detection algorithms is seriously influenced by radiometric difference, registration error and the determination of classification threshold for a different image, and it is difficult to differentiate the true changes of interest from various kinds of detected changes. Therefore, a novel two-step change detection algorithm combining feature-level and pixel-level techniques is proposed to detect changes of man-made objects in multi-temporal remote sensing images. Large-size images are divided into overlapping sub-images, and the changed regions containing man-made objects are extracted by supervised sub-image classification, Then, a pixel-level change detection algorithm is developed to obtain quantitative detection results. Experimental results demonstrate the feasibility and effectiveness of the proposed algorithm.