高分辨率SAR遥感影像道路提取综述

doi:10.13474/j.cnki.11-2246.2025.1002

摘要/Abstract

摘要： 鉴于光学遥感影像在夜晚或光照不足条件下,道路提取效果不佳的问题,本文介绍了基于半自动和全自动的SAR遥感影像道路提取方法,以及基于判别模型和生成模式的深度学习的SAR遥感影像道路提取方法,总结了它们的技术原理与适用场景,分析了各类方法在提取精度、计算复杂度及泛化能力方面的优势与局限,为复杂环境下的道路提取任务提供了技术参考。本文同时指出,在提升SAR遥感影像道路提取效果方面,知识蒸馏、扩散模型辅助标注及大模型架构等技术将具有很大的潜力。

关键词: 合成孔径雷达, 道路提取, 半自动方法, 全自动方法, 判别模型, 生成模型

Abstract: In view of the poor performance of optical remote sensing images in road extraction at night or under insufficient lighting conditions, this paper introduces SAR images road extraction methods based on semi-automatic and fully automatic approaches, as well as deep learning methods based on discriminative models and generative models.It summarizes their technical principles and applicable scenarios, analyzes the advantages and limitations of various methods in terms of extraction accuracy, computational complexity, and generalization, which provides technical references for road extraction based on SAR in complex environments.Meanwhile, in order to improve the effect of road extraction based on SAR, it is pointed out that the technologies of knowledge distillation, diffusion model-assisted annotation and large model architectures will have great potential.

Key words: SAR, road extraction, semi-automatic methods, fully automatic methods, discriminative models, generative models

中图分类号:

P237

姜凯鑫, 宋树华, 毛健, 孙振, 郭国龙, 董丽, 郭辉. 高分辨率SAR遥感影像道路提取综述[J]. 测绘通报, 2025, 0(10): 7-13,19.

JIANG Kaixin, SONG Shuhua, MAO Jian, SUN Zhen, GUO Guolong, DONG Li, GUO Hui. Review of road extraction from high-resolution SAR images[J]. Bulletin of Surveying and Mapping, 2025, 0(10): 7-13,19.

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