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Keywords = MMRS image registration

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31 pages, 3898 KiB  
Review
Multimodal Remote Sensing Image Registration Methods and Advancements: A Survey
by Xinyue Zhang, Chengcai Leng, Yameng Hong, Zhao Pei, Irene Cheng and Anup Basu
Remote Sens. 2021, 13(24), 5128; https://doi.org/10.3390/rs13245128 - 17 Dec 2021
Cited by 65 | Viewed by 9909
Abstract
With rapid advancements in remote sensing image registration algorithms, comprehensive imaging applications are no longer limited to single-modal remote sensing images. Instead, multi-modal remote sensing (MMRS) image registration has become a research focus in recent years. However, considering multi-source, multi-temporal, and multi-spectrum input [...] Read more.
With rapid advancements in remote sensing image registration algorithms, comprehensive imaging applications are no longer limited to single-modal remote sensing images. Instead, multi-modal remote sensing (MMRS) image registration has become a research focus in recent years. However, considering multi-source, multi-temporal, and multi-spectrum input introduces significant nonlinear radiation differences in MMRS images for which researchers need to develop novel solutions. At present, comprehensive reviews and analyses of MMRS image registration methods are inadequate in related fields. Thus, this paper introduces three theoretical frameworks: namely, area-based, feature-based and deep learning-based methods. We present a brief review of traditional methods and focus on more advanced methods for MMRS image registration proposed in recent years. Our review or comprehensive analysis is intended to provide researchers in related fields with advanced understanding to achieve further breakthroughs and innovations. Full article
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