Signal Processing, Image Processing and Fusion Techniques in Remote Sensing
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".
Deadline for manuscript submissions: closed (31 July 2025) | Viewed by 1863
Special Issue Editor
Interests: image processing; signal processing; machine learning; signal, image and video processing; remote sensing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Remote sensing is a vast area for scientific research for numerous important reasons. Primarily, it concerns various remotely sensed areas, encompassing land cover, sea states or types of specific targets that need to be detected or described based on their structure and properties. Furthermore, remote sensing may comprise other objects, such as clouds or planetary surfaces, or even solar physics. Moreover, novel techniques are also being applied in this field for sophisticated target representation (SAR interferometric or SAR tomography).
Since many different sensors are involved in remote sensing, researchers have to be mindful of the physics of each sensor. This is vital for fully utilizing the acquired information. In most applications, the registration of images comes first, enabling the researcher to carry out information fusion or employ super-resolution techniques. Furthermore, registration is necessary in interferometric or tomographic representations.
Accordingly, it is expected that the proposed techniques will contribute to improving our understanding of the investigated areas and provide applicable scientific and commercial results.
Potential topics include, but are in no way limited to, the following:
- Data fusion techniques;
- Decision fusion;
- Classification for remote sensing;
- Pattern recognition for remote sensing;
- Signal and image analysis;
- Image segmentation, enhancement and restoration;
- Machine learning, artificial intelligence and deep learning;
- Filtering processing;
- Remote sensing procedures and applications;
- Analysis of SAR, multispectral and hyperspectral signals;
- Analysis of meteorological data and signals;
- Remote sensing of ocean, ice, land and atmosphere;
- Inverse problems;
- Optimization techniques;
- Target detection;
- Interferometric SAR;
- Tomographic SAR;
- Registration of different types of information;
- Super-resolution techniques.
Dr. Georgia Koukiou
Guest Editor
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
- multichannel information
- sensor types
- signal processing
- image processing
- information fusion
- registration
- elevation models
- target detection
- surface characterization
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