欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
针对遥感图像数据量大、类别归属复杂的特点,提出了一种用于遥感图像分割的原型提取谱聚类算法。该算法首先采用广义模糊c-均值聚类算法对遥感图像进行过分割,将得到的聚类中心作为每个分割区域的代表点;然后,通过构造代表点之间的相似性矩阵,利用谱图划分方法对代表点进行聚类;最后,根据代表点的聚类结果对图像像素点进行重新归类来获得遥感图像的最终分割结果。此算法涉及到3个参数,为了克服算法对于参数的敏感性和内在的随机性,进一步引入集成策略,给出了原型提取谱聚类的集成算法。
英文摘要：
Aiming at the huge data amount and pixel complex ownership of remote sensing images,a prototypes-extraction spectral clustering algorithm for remote sensing image segmentation was proposed.Firstly,the generalized fuzzy c-means algorithm was adopted to perform an over-segmentation of the image,and the obtained clustering prototypes were regarded as the representative points of segmentation regions to reduce the data amount of original image.Secondly,the similarity matrix between the representative points was constructed,and then the spectral graph partitioning method was utilized to cluster the representative points.Eventually,based on the clustering result of representative points,the image pixels were reclassified to obtain the final image segmentation results.There are three parameters in the prototypes-extraction spectral clustering algorithm.In order to overcome the parameter sensitivity and inherent randomness of this method,an ensemble strategy was further introduced into the method and its ensemble algorithm is presented.The segmentation experiments on artificial texture and remote sensing images show that this proposed ensemble method behaves well in segmentation performance.
同期刊论文项目
同项目期刊论文
期刊信息
位置：