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Multimodal Remote Sensing Image Registration Methods and Advancements: A Survey.

Authors :
Zhang, Xinyue
Leng, Chengcai
Hong, Yameng
Pei, Zhao
Cheng, Irene
Basu, Anup
Source :
Remote Sensing; Dec2021, Vol. 13 Issue 24, p5128-N.PAG, 1p
Publication Year :
2021

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 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
13
Issue :
24
Database :
Complementary Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
154458412
Full Text :
https://doi.org/10.3390/rs13245128