杭州师范大学学报（自然科学版）2016，Vol.15Issue(2)：203-207,5.DOI:10.3969/j.issn.1674-232X.2016.02.015
基于小波变换和 K-means 算法的遥感影像分类
Remote Sensing Image Classification Based on Wavelet Transform and K-means Algorithm
摘要
Abstract
On the basis of studying the K‐means clustering algorithm ,combine wavelet transform is combined with K‐means algorithm for remote sensing image classification to improve the classification accuracy of remote sensing image . Fuxian Lake area in Yuxi city of Yunnan Province is taken as a study area ,combined with the specific circumstances of the area ,the optimal bands combination of remote sensing image is obtained according to the OIF calculation .Through the two‐dimensional wavelet decomposition of various terrain samples and remote sensing image , the sample feature vector is obtained .Using K‐means algorithm with the sample feature vector for classifying the remote sensing image ,the result of image classification is got and the accuracy is verified .Comparing with the classification result using K‐means algorithm simply ,the results show that its overall accuracy and Kappa coefficient are 83 .74% and 0 .7753 respectively ,increasing by 14 .26% ,0 .1697 .Especially the classification accuracy of forest land ,bare land and farmland is greatly improved .关键词
遥感影像分类/小波变换/K均值算法Key words
remote sensing image classification/wavelet transform/K-means algorithm分类
计算机与自动化引用本文复制引用
纵清华,王志宇,过仲阳,马品..基于小波变换和 K-means 算法的遥感影像分类[J].杭州师范大学学报（自然科学版）,2016,15(2):203-207,5.基金项目
国家自然科学基金项目（J1310028）． （）
