基于图像的海岸带高度数据测量方法仿真  

Simulation of Data Measurement Method for Coastal Zone Height Based on Images

作　　者：高彦卿[1] 褚龙现[2] 

机构地区：[1]南阳理工学院软件学院,河南南阳473004 [2]平顶山学院软件学院,河南平顶山467000

出　　处：《计算机仿真》2014年第2期411-414,共4页Computer Simulation

摘　　要：研究遥感图像的海岸带高度准确测量问题。由于海岸带的遥感图像数据中有较大的差异性,造成图像中高度点离散度高。以传统云计算为主的海岸带遥感图像高度测量中,不同分辨率图像会造成和高度点相关的云像素数据离散化,在时间尺度上不收敛,测量结果出现偏差。提出了一种带有融合功能的云计算海岸带高度测量方法。建立经验模式分解模型,将海岸带遥感图像进行分解处理,从而为海岸带图像的融合提供基础数据。利用拉普拉斯能量和算法,对海岸带图像进行融合,完成高度测量数据的测量。实验结果表明,改进算法配合云计算对海岸带高度测量数据进行测量,可以对海岸带遥感图像进行有效的融合,极大的提高了数据测量的准确性,为测绘事业的发展提供了良好的基础。In this paper, the problem of high accurate measurement for coastal zone of remote sensing images was researched. We presented a measurement method for the height of coastal zone based on the cloud computing algorithm which has the fusion function. In this method, the EMD model was established firstly to make deposition for coastal zone remote images which provided the basic data to the image fusion of coastal zone. Through the utilization of laplacian smoothing, the image fusion of coastal zone was conducted and the height measurement was completed. Using the Laplace energy and algorithm, the coastal zone images were fused, and the height data were measured. The experimental results show that the improved algorithm can effectively make fusion of remote sensing images, greatly improve the accuracy of the data measurement, which lays a good foundation for the development of surveying and mapping.

关 键 词：云计算 高度测量 数据测量 图像融合 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]