计算机技术与发展2024，Vol.34Issue(5)：37-43,7.DOI:10.20165/j.cnki.ISSN1673-629X.2024.0038
一种新的高光谱遥感图像超像素分割方法
A New Superpixel Segmentation Method for Hyperspectral Remote Sensing Images
摘要
Abstract
In order to solve the problem of low segmentation accuracy of simple linear iterative clustering algorithm in hyperspectral remote sensing image superpixel segmentation tasks,a new unsupervised hyperspectral remote sensing image superpixel segmentation method based on multi-level linear iterative clustering combined with improved label propagation algorithm(LPA)is proposed.Firstly,we expand the applicability of Simple Linear Iterative Clustering(SLIC)to perform superpixel initial segmentation on hyperspectral images through multiple channels,and then perform multi-level iterative and detailed segmentation on superpixels with large color standard deviations.A texture feature extraction method based on local binary mode for hyperspectral remote sensing images is introduced to calculate the texture features of hyperspectral images and fuse multiple spectral features to calculate the similarity between superpixels to construct a weighted graph network,Finally,the LPA community discovery method is improved for superpixel merging,and the improved label propagation algorithm is applied to superpixel merging to obtain a more stable and accurate superpixel merging effect,im-proving the accuracy of superpixel segmentation.Compared with various methods,the proposed method has more accurate superpixel seg-mentation results for hyperspectral remote sensing images,and the superpixel edges are more closely aligned with the real boundary of land objects.It can effectively improve the problem of low accuracy in superpixel segmentation of hyperspectral remote sensing images.关键词
高光谱遥感图像/超像素分割/社区发现/标签传播算法/简单线性迭代聚类Key words
hyperspectral remote sensing images/superpixel segmentation/community discovery/label propagation algorithm/simple linear iterative clustering分类
信息技术与安全科学引用本文复制引用
杨洋,刘思樊,童恒建..一种新的高光谱遥感图像超像素分割方法[J].计算机技术与发展,2024,34(5):37-43,7.基金项目
国家自然科学基金资助项目(41171339,U1803117) （41171339,U1803117）
