基于自动多种子区域生长的遥感影像面向对象分割方法

在遥感影像分割分类中,种子区域生长算法是一种常见的分割算法.传统的种子区域生长算法只能提取单一连续的、纹理简单的目标地物,而对具有复杂纹理和多光谱特征的遥感影像,分割时存在分割效果差、不能同时有效地提取多个地物的问题.针对以上问题,本文提出了一种改进的面向对象的自动多种子区域生长算法.该方法适用于同时提取多个目标地物,且分割效果好.该方法首先使用一种改进的中值滤波对影像进行平滑处理,使目标内部一致性更高,同时保留纹理信息.然后通过一定的准则进行自动种子选取并进行生长,最后对生长后的区域进行碎斑合并处理,最终得到多种对象的分割结果.本文采用三组不同大小的1m空间分辨率的航空影像进行实验,通过与分水岭以及传统单种子区域生长算法的多组实验对比,发现该方法可以面向全局对象,自动选取覆盖各种地物类型的种子,同时对多种地物目标进行分割处理,可为后续面向对象影像分析和应用提供可靠的数据基础.

Object-oriented remote sensing image segmentation based on automatic multiseed region growing algorithm

For the segmentation of a remote sensing image,the seeded region growing algorithm is a common method. The tradi-tional single-seed region growing algorithm can only segment a remote sensing image in a single,continuous object with simple texture. However,in the case of a high-resolution remote sensing image with complex texture and multispectral features,the segmentation result of this algorithm is unsatisfactory,as it cannot segment multiple objects simultaneously and effectively. To solve this problem,this pa-per proposes an improved object-oriented automatic multiseed region growing algorithm,which is suitable for simultaneously extracting multiple target objects and its segmentation result is also good. The method first uses an improved median filter to smooth the image, making the interior of the multiple target objects homogeneous,while preserving their texture. Then,it automatically selects the multi-ple seed regions through a certain criterion and finally,processes the grown regions and combines them. Thus,this paper obtains the segmentation results of various objects. The paper uses three sets of aerial images with different spatial resolutions to carry out experi-ments. Compared with watershed algorithm and traditional single-seed region growing algorithm,this method can be used for global ob-jects. It can automatically select different types of seeds with multiple features and can simultaneously segment multiple target objects, thus providing a reliable data for the object-oriented image analysis and application.