基于SAR和多光谱图像融合的城市浅埋裂缝检测

Le Yu, Dengrong Zhang, Wei Zhang, Qin Huang
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引用次数: 0

摘要

城市及其周边区域裂缝的研究是一个重要的课题。卫星遥感影像可以从宏观上说明区域裂缝和构造的全貌。多源图像(特别是SAR与光学多光谱图像)的融合是遥感信息处理和应用领域的一个热点。提出了一种基于图像融合的线性结构信息检测方法。介绍了小波变换和小波包变换及其在图像融合中的应用,提出了一种区域标准差小波系数融合方法。实验结果表明,在Radarsat SAR与Landsat MSS、ETM+多光谱遥感图像融合中,小波包融合的分辨率增强效果优于小波融合。对杭州地区第四纪松散沉积物覆盖的浅埋区域裂缝信息的勘探研究表明,将SAR与光学多光谱RS图像融合,可以提高浅埋裂缝的分辨率和解译能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SAR and multi-spectral images fusion for shallow-buried fracture detection in urban area
Exploring the regional fractures in urban area and its surroundings is an important issue. Satellite remote sensing image can be used to illustrate the panorama of regional fractures and structures on macroscopic view. Fusion of multi-source images(especially SAR and optical multi-spectral image) is a hot spot in RS information processing and application field. A image fusion based linear structure information detection method is proposed in this paper. After introducing wavelet and wavelet packet transform and their applications in image fusion, a regional standard deviation wavelet coefficients fusion method is proposed. Experimental result shows wavelet packet fusion is better than wavelet fusion in resolution enhancement for fusion of Radarsat SAR and Landsat MSS, ETM+ multispectral remote sensing images. Study of exploring shallow-buried regional fracture information covered by Quaternary unconsolidated sediments in Hangzhou area shows the fusion method applied on SAR and optical multi-spectral RS image can improve resolution and the capability of interpret shallow-buried fractures.
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