Su Nan, Yan Yiming, Qiu Mingjie, Zhao Chunhui, Wang Liguo
College of information and communication engineering, Harbin Engineering University, Harbin 150001, China.
School of electronics and information engineering, Harbin Institute of Technology, Harbin 150001, China.
Sensors (Basel). 2018 Mar 29;18(4):1035. doi: 10.3390/s18041035.
In this paper, we proposed a novel object-based dense matching method specially for the high-precision disparity map of building objects in urban areas, which can maintain accurate object structure characteristics. The proposed framework mainly includes three stages. Firstly, an improved edge line extraction method is proposed for the edge segments to fit closely to building outlines. Secondly, a fusion method is proposed for the outlines under the constraint of straight lines, which can maintain the building structural attribute with parallel or vertical edges, which is very useful for the dense matching method. Finally, we proposed an edge constraint and outline compensation (ECAOC) dense matching method to maintain building object structural characteristics in the disparity map. In the proposed method, the improved edge lines are used to optimize matching search scope and matching template window, and the high-precision building outlines are used to compensate the shape feature of building objects. Our method can greatly increase the matching accuracy of building objects in urban areas, especially at building edges. For the outline extraction experiments, our fusion method verifies the superiority and robustness on panchromatic images of different satellites and different resolutions. For the dense matching experiments, our ECOAC method shows great advantages for matching accuracy of building objects in urban areas compared with three other methods.
在本文中，我们提出了一种新颖的基于对象的密集匹配方法，专门用于生成城市区域中建筑物对象的高精度视差图，该方法能够保持准确的对象结构特征。所提出的框架主要包括三个阶段。首先，针对边缘线段提出了一种改进的边缘线提取方法，以使边缘紧密贴合建筑物轮廓。其次，提出了一种在直线约束下的轮廓融合方法，该方法能够保持具有平行或垂直边缘的建筑物结构属性，这对于密集匹配方法非常有用。最后，我们提出了一种边缘约束与轮廓补偿（ECAOC）密集匹配方法，以在视差图中保持建筑物对象的结构特征。在所提出的方法中，改进后的边缘线用于优化匹配搜索范围和匹配模板窗口，高精度的建筑物轮廓用于补偿建筑物对象的形状特征。我们的方法可以大大提高城市区域中建筑物对象的匹配精度，尤其是在建筑物边缘处。对于轮廓提取实验，我们的融合方法在不同卫星和不同分辨率的全色图像上验证了其优越性和鲁棒性。对于密集匹配实验，与其他三种方法相比，我们的ECOAC方法在城市区域建筑物对象的匹配精度方面显示出巨大优势。
