Special Issue "Knowledge-Driven and/or Data-Driven Methods for Remote Sensing Image Processing"
Deadline for manuscript submissions: 31 May 2024 | Viewed by 1328
Interests: machine learning; hyperspectral unmixing of remote sensing images; remote sensing image fusion; data mining; intelligent computing
Special Issues, Collections and Topics in MDPI journals
Interests: hyperspectral image processing; machine learning; scientific computing
Interests: image processing; optimization; artificial intelligence; scientific computing; computer vision; machine learning; inverse problems
Interests: hyperspcetral image processing; machine learning
Interests: remote sensing; image processing; signal processing; pattern recognition; classification and fusion of multisource remote sensing data; multi-temporal image analysis; biophysical parameter estimation
Remote sensing image processing plays a critical role in diverse fields such as environmental monitoring, resource management, and disaster response. However, processing and analyzing remotely sensed data can be challenging due to complex environments, limited signal-to-noise ratio, and the presence of noise and artifacts. Recently, two different approaches to remote sensing image processing have emerged: knowledge-driven and data-driven methods. Among these, the knowledge-driven methods, based on expert experience or mathematical models describing the physical processes underlying remote sensing data, show high interpretability. In contrast, data-driven methods leverage machine learning algorithms to identify correlations and patterns from observed data, which are prevalent in recent years. In particular, this Special Issue focuses on exploring the advantages and limitations of knowledge-driven and data-driven approaches and suggesting ways to combine them to boost remote sensing image processing. We are looking forward to receiving a variety of works on this topic, whether they are theoretical or heuristic. This Special Issue is expected to leverage the strengths of knowledge-driven and data-driven methods and provide valuable insights into developing better remote sensing techniques for a broad range of applications.
Topics of interest include, but are not limited to, the following points:
- General remote sensing image processing, such as classification, object detection, segmentation, super-resolution, denoising, etc.
- Real-world applications based on remote sensing images, such as land use mapping, vegetation analysis, and environmental monitoring.
- Combining traditional methods and deep learning methods for remote sensing image processing and analysis.
- Multi-modal remote sensing image processing, such as multi-modal image fusion, pan-sharpening, etc.
Prof. Dr. Junmin Liu
Prof. Dr. Xile Zhao
Prof. Dr. Tieyong Zeng
Dr. Bin Zhao
Dr. Claudia Paris
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.
- image processing
- remote sensing
- knowledge-driven methods
- data-driven methods