基于k-mask的超连通理论及应用  

Theory and application of k-mask based hyper-connectivity

作　　者：才辉[1,2] 蔡晋辉[3] 张光新[2] 侯迪波[2] 周泽魁[2] 

机构地区：[1]福建省中心检验所国家电子信息产品质量监督检验中心,福建福州350002 [2]浙江大学工业控制技术国家重点实验室,浙江杭州310027 [3]中国计量学院计量测试工程学院,浙江杭州310018

出　　处：《吉林大学学报（工学版）》2010年第1期201-206,共6页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金项目(50505045)

摘　　要：为了综合利用目标的多种信息进行融合,增强滤波效果,提出了一种新的基于k-mask的超连通类。通过不同的通道信息和约束条件得到连通掩模图、模板图,由连通掩模图与模板图相交部分的面积信息重新标识模板图中的连通成分,经过选择和聚类形成新的连通空间。根据基于k-mask超连通类的定义设计二值超连通开算子和超连通重构算子,并将其分别应用于字符区域的标识和遥感图像主干道路的提取。实验表明,通过灵活选择连通掩模,融合图像多梯度信息、颜色信息和多通道信息,有效地改善了传统开算子和重构算子的滤波性能。In order to fuse efficiently the multi-channel information of the target and improve the performance of the filter, a new class of k-mask based hyper-connectivity was proposed. The connectivity mask image and the reconstruct mask image were obtained from the different channel informations and restraint conditions. According to the area information by which the connectivity mask image intersects the reconstruct mask image, the connected components in the reconstruct mask image were relabeled to form the new connection space by selection and aggregation. From the definition of the hyper-connectivity class, k mask based hyper connected open operator and reconstruct operator were designed and applied in labeling the character region and extracting the major path of the remote sensing image. Experiment results illustrated that the filter performance of the traditional open operator and reconstruction operator was improved significantly by flexible selection of the connectivity mask image and fusion of the image multi-gradient information, color information and multi-channel information.

关 键 词：计算机应用 连通算子 超连通 重构算子 图像分割 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]