Intelligent Processing and Analysis of Multi-modal Remote Sensing Data
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 31 October 2024 | Viewed by 241
Special Issue Editors
Interests: image processing; pattern recognition; computer vision; machine learning; remote sensing; aerospace exploration
Special Issues, Collections and Topics in MDPI journals
Interests: hyperspactral image analysis; machine learning; deep learning techniques; dimensionality reduction; super-resolution; spectral unmixing; data fusion
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The processing and automatic interpretation of the extensive remote sensing data obtained by satellites in orbit, near-space vehicles or manned/unmanned aerial vehicles (UAV) has always been a popular topic in the field of remote sensing. In recent years, artificial intelligence (AI) technology, especially deep learning, has developed rapidly and significantly accelerated research in a range of areas. Intelligent processing and analysis have extensive applicative potential in multiple remote sensing data, including panchromatic, multispectral, hyperspectral, infrared, SAR, LiDAR, etc. This Special Issue aims to compile recent works in this field that provide methodological contributions and innovative applications. Novel research that employs intelligent methods to address practical problems in remote sensing applications is also welcome. The scope of this Special Issue includes, but is not limited to, the following topics:
- Intelligent image processing for remote sensing, including restoration (denoising, deblurring and dehazing), super-resolution, enhancement, registration, pan-sharpening, etc.;
- Unsupervised/weakly-supervised/self-supervised learning for image processing and analysis of remote sensing data;
- Data fusion/multi-modal data analysis;
- Domain adaption for cross-modal data analysis;
- AI methods for image/scene classification;
- AI methods for target detection/recognition/tracking;
- Cloud detection and removal in remote sensing images;
- Change detection/semantic segmentation for remote sensing;
- Large models for remote sensing;
- Deep learning for remote sensing applications.
Dr. Haopeng Zhang
Dr. Giorgio Licciardi
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
- remote sensing
- image processing
- image analysis
- artificial intelligence
- deep learning
- data fusion
- multispectral and hyperspectral data
- synthetic aperture radar
- LiDAR
