Vectorization of Raster Data and Solution to Relevant Problems

Raster and vector are two major types of data format in GIS, especially at presenst, remote sensing images have been very important data resource of GIS. With the development of GIS, remote sensing data will play an even greater role in GIS. But however, remote sensing data is usually raster data, and cannot meet the requirements of spatial analysis in GIS, so a conversion of raster data into vector one is of great importance for GIS. Although there are many algorithms and softwares for vectorization of raster data, yet some problems still exist in the process of vectorizing raster data, for example, the vector images thus produced have some islands and self-intersect polygons, or there are only polylines without good topological relation. Hence this can hardly gratify the need of our work.On the basis of summarizing the existing algorithms and following the topological theory, an improved method for converting raster data to vector one is suggested in this paper. In other words, firstly it's determined by the relation of similarities or differences between four neighboring pixels(Fig.2) whether the crosses of neighboring pixels(Fig.1) belong to nodes or coordinate points, then in the process of searching nodes and coordinate points, both vertical and horizontal line segments are picked up at the same time in order to realize the vectorization of raster data more quickly and more efficiently. In addition, by use of the methods such as automatically breaking and widening grid size, some common problems in the course of vectorization of raster data such as self-intersected polygon and island are successfully solved. The authors programme a programme in Visual C++ to realize the algorithm in this paper, and contrast its result with other softerwares or algorithms. The algorithm has some better virtues:1)it is easy and convenient to practice; and 2) it has perfect topological relation. Therefore, the improved method is of great benefit to retrieve useful information from remote sensing images, and to promote the integration of Remote Sensing and Geography Information System.