Guided Superpixel Method for Topographic Map Processing
Guided Superpixel Method for Topographic Map Processing
复制标题
地形图处理的引导超像素方法
DOI：
10.1109/tgrs.2016.2567481
复制
发表时间：
2016-11-01
影响因子：
8.2
通讯作者：
Yang, Yun
中科院分区：
文献类型：
--
作者：
Miao, Qiguang;Liu, Tiange;Yang, Yun
超像素被广泛应用于计算机视觉和图像处理任务中，但由于地形图中地理元素分布复杂，在地形图处理中应用较少。提出了一种基于引导分水岭变换（GWT）的超像素生成方法。在使用GWT之前，需要获得地理元素分布的线索以及不同元素之间的边界。提出了一种基于复合反向高斯滤波和剪切变换的线性特征提取方法来获取分布信息。同时，采用一种基于视觉系统颜色对抗机制的边界检测方法来获取边界信息。然后，将线性特征和边界输入到最终的分割过程中，以获得超像素。实验结果表明，该方法在形状控制、尺寸控制和边界粘附等方面具有较好的性能，是所有比较方法中最经典和最先进的。此外，我们通过实验验证了该方法的低复杂度和低内存成本，使处理大比例尺地形图成为可能。
Superpixels have been widely used in lots of computer vision and image processing tasks but rarely used in topographic map processing due to the complex distribution of geographic elements in this kind of images. We propose a novel superpixel-generating method based on guided watershed transform (GWT). Before GWT, the cues of geographic element distribution and boundaries between different elements need to be obtained. A linear feature extraction method based on a compound opposite Gaussian filter and a shear transform is presented to acquire the distribution information. Meanwhile, a boundary detection method, which based on the color-opponent mechanisms of the visual system, is employed to get the boundary information. Then, both linear features and boundaries are input to the final partition procedure to obtain superpixels. The experiments show that our method has the best performance in shape control, size control, and boundary adherence, among all the comparison methods, which are classic and state of the art. Furthermore, we verify the low complexity and low cost of memory in our method through experiments, which makes it possible to deal with large-scale topographic maps.