人民黄河Issue(3)：10-12,3.DOI:10.3969/j.issn.1000-1379.2014.03.004
基于遥感图像的河流提取方法及应用研究
Research on Application of the River Extraction Method Based on Remote Sensing Image
摘要
Abstract
A river extraction algorithm based on color remote sensing images through fusing the detection outputs of supervised classification method and unsupervised clustering method was proposed. In the supervised classification method,using the local Fourier transform to capture discrimina-tive texture and color representation. Then used the local Fourier transform features extracted from labeled samples to train a large margin nearest neighbor classifier for classifying image pixels into two classes:river and backgrounds. In unsupervised clustering method,k-means clustering was adopted for color-based segmentation to separate river areas from backgrounds. Finally,the outputs of the two methods were fused to obtain detec-tion result. The results show that this method can extract the river from the color remote sensing image accurately.关键词
k-均值分类/局部傅里叶变换/图像分割/河流提取/遥感图像Key words
k-means clustering/local Fourier transform/image segmentation/river extraction/remote sensing image分类
信息技术与安全科学引用本文复制引用
付晓,严华,贺新..基于遥感图像的河流提取方法及应用研究[J].人民黄河,2014,(3):10-12,3.基金项目
国家自然科学基金资助项目（61172181）。 （）
