基于主题模型的高分辨率遥感影像解译综述
Topic Model for High Resolution Remote Sensing Data Interpretation:A Review
李真 1朱祺琪 1雷洋 1万江琴 1王琳琳 1许磊1
作者信息
- 1. 中国地质大学(武汉)地理与信息工程学院,国家地理信息系统工程技术研究中心,湖北 武汉 430078
- 折叠
摘要
从文本分析到影像解译,主题模型一直起着十分重要的作用.由于其强大的语义挖掘能力,主题模型能够捕捉遥感影像中潜在的空谱信息,从而广泛应用于遥感影像解译问题(例如语义分割、目标检测、场景分类等).然而,目前还没有一个详述和总结主题模型在遥感影像中应用现状的研究.本研究旨在系统地总结主题模型在遥感影像中的应用,并针对几个的典型影像解译任务开展实验对比和分析,全文架构包括以下4个方面:①主题模型基本理论;②基于主题模型的遥感影像典型应用;③基于主题模型的实验对比分析;④总结和展望.
Abstract
From text analysis to image interpretation,the Topic Model(TM)consistently plays a pivotal role.With its robust semantic mining capabilities,topic model can effectively capture latent spectral and spatial infor-mation from Remote Sensing(RS)images.Recent years have seen the widespread adoption of topic models to address challenges in RS image interpretation,including semantic segmentation,target detection,and scene classification.Thus,clarifying and summarizing the present application status of topic models in remote sensing imagery is pivotal for advancing remote sensing image interpretation technology.This paper initially presents the foundational theory of topic models,followed by a systematic overview of their typical applications in re-mote sensing imagery.In addition,experimental comparisons and analyses are performed across various typical remote sensing image interpretation tasks,illustrating the extensive applicability of topic models in the realm of remote sensing and the efficacy of distinct topic models in enhancing our comprehension of remote sensing imag-ery.Subsequently,we have outlined the limitations of topic models and explored the potential and prospects of integrating them with deep learning.
关键词
主题模型/遥感影像/场景分类/语义分割Key words
Topic model/Remote sensing image/Scene classification/Semantic segmentation引用本文复制引用
基金项目
中国地质大学(武汉)国家地理信息系统工程技术研究中心开放基金(2023KFJJ01)
国家重点研发计划(2022YFB3903402)
国家科研基金项目面上项目(42271413)
出版年
2024
NETL
NSTL
万方数据