计算机应用与软件2025，Vol.42Issue(4)：229-236,288,9.DOI:10.3969/j.issn.1000-386x.2025.04.033
融合各向异性上下文的遥感图像语义分割
SEMANTIC SEGMENTATION OF REMOTE SENSING IMAGES BY FUSING ANISOTROPIC CONTEXT
摘要
Abstract
Due to the anisotropic distribution of ground targets in remote sensing images,such as large variation of aspect ratio and wide range of target scale,the existing segmentation methods are still insufficient for the segmentation ability of targets with long-range banded structure and dense discrete distribution objects.In order to solve this problem,a remote sensing image segmentation network integrating anisotropic context is proposed.The network extracted the gradient information of the target by imposing a priori constraints on the gradient convolution kernel parameters,optimized the segmentation edge.It designed modules such as multiscale parallel dilated convolution and anisotropic target composite strip pooling module,and captured the anisotropic context information of different scale targets in remote sensing images.The multi-scale context information was fused and the image details were restored.Experiments on the public Potsdam and Vaihingen datasets show that the anisotropic context fusion network in this paper is superior to the advanced segmentation networks such as DaNet,DeepLabv3+and Eanet,and the ablation experiment also verifies the effectiveness of each module of the network in this paper.关键词
遥感图像/语义分割/各向异性上下文/梯度卷积/复合条状池化Key words
Remote sensing image/Semantic segmentation/Anisotropic context/Gradient convolution/Composite strip pooling分类
信息技术与安全科学引用本文复制引用
岳志远,耿玉标,闫宏艳,孙玉宝..融合各向异性上下文的遥感图像语义分割[J].计算机应用与软件,2025,42(4):229-236,288,9.基金项目
国家自然科学基金项目(U2001211). （U2001211）
