Linear Feature Separation from Topographic Maps Using Energy Density and the Shear Transform
Linear Feature Separation from Topographic Maps Using Energy Density and the Shear Transform
复制标题
使用能量密度和剪切变换从地形图中分离线性特征
DOI：
10.1109/tip.2012.2233487
复制
发表时间：
2013-04-01
影响因子：
10.6
通讯作者：
Li, Weisheng
中科院分区：
文献类型：
--
作者：
Miao, Qiguang;Xu, Pengfei;Li, Weisheng
在彩色扫描地形图中，线状地物很难从复杂的背景中分离出来，特别是当某些特定图像中线状地物的颜色与背景颜色接近时。本文提出了一种基于能量密度和剪切变换的线与背景分离方法。首先，引入了剪切变换，可以添加线条的方向特征，以克服在仅在一个方向上的图像中使用分离方法会发生线性信息丢失的缺点。然后，由于负像中线条的能量集中度通常高于背景，因此建立水平和垂直方向的模板以将线条与背景分开。此外，剩余的网格背景可以通过网格模板匹配来擦除。根据连通区域面积测量，去除仅包含一个像素或少于十个像素的孤立斑块。最后，利用并集操作，不同剪切图像中获得的线性特征可以相互补充，从而使最终结果的线条更加完整。该方法的基本性质是引入能量密度而不是传统方法中常用的颜色信息。实验结果表明，该方法能够更有效地将线状特征与背景区分开来，并且能够通过剪切变换改变线状特征，获得良好的效果。
Linear features are difficult to be separated from complicated background in color scanned topographic maps, especially when the color of linear features approximate to that of background in some particular images. This paper presents a method, which is based on energy density and the shear transform, for the separation of lines from background. First, the shear transform, which could add the directional characteristics of the lines, is introduced to overcome the disadvantage that linear information loss would happen if the separation method is used in an image, which is in only one direction. Then templates in the horizontal and vertical directions are built to separate lines from background on account of the fact that the energy concentration of the lines usually reaches a higher level than that of the background in the negtive image. Furthermore, the remaining grid background can be wiped off by grid templates matching. The isolated patches, which include only one pixel or less than ten pixels, are removed according to the connected region area measurement. Finally, using the union operation, the linear features obtained in different sheared images could supplement each other, thus the lines of the final result are more complete. The basic property of this method is introducing the energy density instead of color information commonly used in traditional methods. The experiment results indicate that the proposed method could distinguish the linear features from the background more effectively, and obtain good results for its ability in changing the directions of the lines with the shear transform.