多时相高分辨率卫星遥感图像语义分割算法

doi:10.13229/j.cnki.jdxbgxb.20240503

吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (6): 2131-2137.doi: 10.13229/j.cnki.jdxbgxb.20240503

多时相高分辨率卫星遥感图像语义分割算法

于营^1,²(),王春平^1,²,寇人可¹,杨博雄²,王雷^3,⁴,赵福军²,付强¹()

^1.陆军工程大学，石家庄 050003
^2.三亚学院容淳铭院士工作站，海南三亚 572022
^3.海南空天信息创新研究院海南省地球观测重点实验室，海南三亚 572029
^4.中国科学院空天信息创新研究院海南省地球观测重点实验室，北京 100094

收稿日期:2024-05-10 出版日期:2025-06-01 发布日期:2025-07-23
通讯作者: 付强 E-mail:yingyu@sanyau.edu.cn;Fu_Qiang@aeu.edu.cn
作者简介:于营（1990-），女，副教授，博士研究生.研究方向：语义分割，计算机视觉.E-mail：yingyu@sanyau.edu.cn
基金资助:
国家重点研发计划项目(2021YFB3901301);海南省院士创新平台专项项目(YSPTZX202145);海南省高等学校教育教学改革研究项目(Hnjg2023ZD-44)

Semantic segmentation algorithm for multi temporal high⁃resolution satellite remote sensing images

Ying YU^1,²(),Chun-ping WANG^1,²,Ren-ke KOU¹,Bo-xiong YANG²,Lei WANG^3,⁴,Fu-jun ZHAO²,Qiang FU¹()

^1.Army Engineering University of PLA，Shijiazhuang 050003，China
^2.Academician Workstation of Chunming Rong，University of Sanya，Sanya 572022，China
^3.Key Laboratory of Earth Observation of Hainan Province，Hainan Aerospace Information Research Institute，Sanya 572029，China
^4.Key Laboratory of Earth Observation of Hainan Province，Aerospace Information Research Institute，Chinese Academy of Sciences，Beijing 100094，China

Received:2024-05-10 Online:2025-06-01 Published:2025-07-23
Contact: Qiang FU E-mail:yingyu@sanyau.edu.cn;Fu_Qiang@aeu.edu.cn

摘要/Abstract

摘要：

为了解决单一时相低分辨率图像无法准确识别遥感图像中各类语义对象的问题，提出了多时相高分辨率卫星遥感图像语义分割算法。通过求解图像信息的多时相分辨率，进行遥感目标分区处理，准确识别并提取遥感图像中各类语义对象及特征；基于尺度函数定义式计算分割权重，实现对遥感图像语义对象的精确识别与分割。实验结果表明，本文方法显著提高了语义对象的识别准确率，分割后地物信息中各项语义对象占比的实验值与真实值之间的最大数值差未超过0.2%，为遥感图像的应用提供了有力支持。

关键词: 多时相高分辨率, 卫星遥感图像, 语义分割, 显著遥感区域, 尺度函数, 分割权重

Abstract:

In order to solve the problem of inaccurate recognition of various semantic objects in remote sensing images using a single temporal low resolution image， a multi temporal high-resolution satellite remote sensing image semantic segmentation algorithm was proposed. By solving the multi temporal resolution of image information， remote sensing targets are partitioned， and various semantic objects and features of remote sensing images are accurately identified and extracted. Based on the definition of scale function， the segmentation weight is calculated to realize accurate recognition and segmentation of semantic objects in remote sensing images. The experimental results show that the recognition accuracy of semantic objects is significantly improved by the proposed method， and the maximum numerical difference between the experimental value and the real value of each semantic object content in the segmented ground object information does not exceed 0.2%， which provides strong support for the application of remote sensing images.

Key words: multi temporal high-resolution, satellite remote sensing images, semantic segmentation, significant remote sensing areas, scale function, segmentation weight

中图分类号:

TN929

于营,王春平,寇人可,杨博雄,王雷,赵福军,付强. 多时相高分辨率卫星遥感图像语义分割算法[J]. 吉林大学学报(工学版), 2025, 55(6): 2131-2137.

Ying YU,Chun-ping WANG,Ren-ke KOU,Bo-xiong YANG,Lei WANG,Fu-jun ZHAO,Qiang FU. Semantic segmentation algorithm for multi temporal high⁃resolution satellite remote sensing images[J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(6): 2131-2137.

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标记	地物信息名称	BRG颜色值
1	背景物	（0，0，0）
2	植物	（127，0，255）
3	建筑结构	（0，255，255）
4	水系结构	（255， 0，191）
5	连通道路	（60，220，20）

多时相高分辨率卫星遥感图像语义分割算法

Semantic segmentation algorithm for multi temporal high⁃resolution satellite remote sensing images

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