Deep Learning for Multimodal Remote Sensing Image Registration
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 30 September 2024 | Viewed by 119
Special Issue Editors
Interests: multimodal image registration; multi-view SAR image registration; 3D reconstruction
Interests: image registration; image matching; image fusion; image segmentation
Special Issues, Collections and Topics in MDPI journals
Interests: objection detection and recognition; multimodal image registration; cross-modal geo-localization
Special Issues, Collections and Topics in MDPI journals
Interests: SAR target detection and recognition; SAR image registration; PolSAR data interpretation
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing image change detection; image segmentation
Special Issue Information
Dear Colleagues,
With the ongoing expansion of Earth observation satellite launches worldwide, a discernible shift towards satellites that are designed for enhanced agility and frequent revisit capabilities is emerging. In the current landscape, we have access to a rich tapestry of multitemporal, multi-view, and multimodal remote sensing data. This data is replete with extensive information, significantly augmenting the scope of Earth observation and subsequently bolstering the efficacy of related remote sensing applications. Image registration stands as an indispensable foundational process, pivotal for unlocking the full potential of these multifaceted data sets. This Special Issue is dedicated to convening a comprehensive array of the most recent breakthroughs, cutting-edge methodologies, and tangible applications of deep learning within the sphere of multimodal remote sensing image registration. It endeavors to delve into the challenges and prospects that arise from the amalgamation of diverse remote sensing data modalities, alongside the deployment of deep learning frameworks aimed at refining the precision and efficiency of image registration processes.
The scope of this Special Issue encompasses all aspects of deep learning for multimodal remote sensing image registration, including, but not limited to, the following:
- Multimodal image registration using deep learning;
- Dataset and evaluation for deep learning-based image registration methods;
- Registration of remote sensing images in challenging scenarios;
- Multimodal data fusion and change detection;
- Remote sensing applications based on deep learning.
Dr. Yuming Xiang
Prof. Dr. Yuanxin Ye
Prof. Dr. Wen Yang
Prof. Dr. Deliang Xiang
Dr. Ling Wan
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- deep learning for remote sensing
- multimodal image registration
- multimodal data fusion
- multimodal change detection
- remote sensing image matching
- unsupervised learning
