本文针对城市建筑物的特点，提出融合 Hessian-Affine和 MSER的仿射协变区域检测方法，利用重复误差筛选高度相关的不同类型区域，根据仿射匹配性分值选择性删除冗余区域，并采用平均重复率、平均匹配区域数进行综合评价分析。实验结果表明，提出的算法将两种检测子互补使用，对于各种仿射变换下的建筑物检测准确率较高，冗余少，适用于城市遥感的实际应用中。Urban Remote Sensing Images

With the development of remote sensing technology, high-resolution urban remote sensing images contain more structural and textural information of buildings. Buildings in urban mostly have clear corners and homogeneous roofregions. However, the instability of imaging conditions usually causes blur, light changes and other affine transformations to remote sensing images. Combined with Hessian-Affine and MSER, a fused affine region detection algorithm is proposed. Regions highly covered by others are selected according to the overlap error. Then these selected regions are considered whether to be deleted according to the affine match score. The building images’ average repeatability and number of correspondence are used for evaluation and analysis on detection. Experiments results show that the proposed method make full use of the two complementary detectors, and it obtains the best average repeatability, less redundancy under the different types of transformations. Therefore, the proposed method is better for urban remote sensing application fields.