摘要
提出一种全色遥感图像中城区的快速模糊分割算法。该算法基于模糊集理论,根据贝叶斯准则建立相应的隶属函数,并分析选取城区在全色图像中有效的特征,逐步实现城区的分割。实验以SPOT-5全色图像为例,并对模糊训练的可靠性进行分析,最后与区域增长法和多尺度几何信息分割算法进行比较。实验表明,该算法简单准确快速,能够为一些重要的应用提供有效支持。
A fast fuzzy algorithm for the segmentation of urban areas especially in panchromatic remote sensing images was proposed. The algorithm was supposed to be an image previous process for the small targets recognition in immense remote sensing images. Based on the fuzzy set theory, a membership function was introduced according to Bayesian criteria. The process of segmentation was achieved gradually by using appropriate features of urban areas. The experiment was implemented on SPOT-5 PAN images and a reliability analysis of the fuzzy membership function was made after the segmentation. Compared with the region growing segmentation method and the algorithm based on multi-scale wavelet geometry information, the experimental results show that this algorithm has good performance with low complexity and high accuracy, and it is an efficient preprocessing technique for some important remote sensing applications.
出处
《计算机应用》
CSCD
北大核心
2008年第12期3112-3115,共4页
journal of Computer Applications
基金
国家863计划项目(2004AA783052)
关键词
贝叶斯准则
模糊隶属度
模糊分割
全色遥感图像
Bayesian criteria
fuzzy membership
fuzzy segmentation
panchromatic remote Sensing image