CDFSL: Image Registration for Spaceborne Hyperspectral and Multispectral Data Having Large Spatial-Resolution Difference-Reference-Cited by-同舟云学术

CDFSL: Image Registration for Spaceborne Hyperspectral and Multispectral Data Having Large Spatial-Resolution Difference

Published:2023 Issue: Volume:61 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Ren Kai¹,Sun Weiwei¹^ORCID,Meng Xiangchao¹^ORCID,Yang Gang²^ORCID,Peng Jiangtao³^ORCID,Huang Jingfeng⁴^ORCID,Li Jiancheng⁵

Affiliation:

1. Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China

2. Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China

3. Hubei Key Laboratory of Applied Mathematics, Faculty of Mathematics and Statistics, Hubei University, Wuhan, China

4. Institute of Applied Remote Sensing and Information Technology, Key Laboratory of Agricultural Remote Sensing and Information System, Zhejiang University, Hangzhou, China

5. School of Geodesy and Geomatics, Wuhan University, Wuhan, China

Funder

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

Public Projects of Ningbo City

Ningbo Science and Technology Innovation 2025 Major Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10160049.pdf?arnumber=10160049

Reference69 articles.

1. A Multiscale Framework With Unsupervised Learning for Remote Sensing Image Registration

2. Unsupervised Multistep Deformable Registration of Remote Sensing Imagery Based on Deep Learning

3. Normalized Total Gradient: A New Measure for Multispectral Image Registration

4. VoxelMorph: A Learning Framework for Deformable Medical Image Registration

5. Robust Matching for SAR and Optical Images Using Multiscale Convolutional Gradient Features

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