Optical and SAR Image Registration in Equatorial Cloudy Regions Guided by Automatically Point-Prompted Cloud Masks

Optical and SAR Image Registration in Equatorial Cloudy Regions Guided by Automatically Point-Prompted Cloud Masks

The equator’s unique combination of high humidity and temperature renders optical satellite imagery highly susceptible to persistent cloud cover. In contrast, synthetic aperture radar (SAR) offers a robust alternative due to its ability to penetrate clouds with microwave imaging. This study addresse...

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Bibliographic Details
Main Authors: Yifan Liao, Shuo Li, Mingyang Gao, Shizhong Li, Wei Qin, Qiang Xiong, Cong Lin, Qi Chen, Pengjie Tao
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Remote Sensing
Subjects:
cloudy equatorial region
optical image
SAR
automatic prompt
cross-modal image matching
Online Access:https://www.mdpi.com/2072-4292/17/15/2630
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Summary:The equator’s unique combination of high humidity and temperature renders optical satellite imagery highly susceptible to persistent cloud cover. In contrast, synthetic aperture radar (SAR) offers a robust alternative due to its ability to penetrate clouds with microwave imaging. This study addresses the challenges of cloud-induced data gaps and cross-sensor geometric biases by proposing an advanced optical and SAR image-matching framework specifically designed for cloud-prone equatorial regions. We use a prompt-driven visual segmentation model with automatic prompt point generation to produce cloud masks that guide cross-modal feature-matching and joint adjustment of optical and SAR data. This process results in a comprehensive digital orthophoto map (DOM) with high geometric consistency, retaining the fine spatial detail of optical data and the all-weather reliability of SAR. We validate our approach across four equatorial regions using five satellite platforms with varying spatial resolutions and revisit intervals. Even in areas with more than 50 percent cloud cover, our method maintains sub-pixel edging accuracy under manual check points and delivers comprehensive DOM products, establishing a reliable foundation for downstream environmental monitoring and ecosystem analysis.
ISSN:2072-4292

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