Advances on Multimodal Signal Processing: Theory and Applications

Dear Colleagues,

Remote sensing is generally defined as the acquisition of information on targets of interest (e.g., objects and/or phenomenon) without physically contacting it. Traditionally, this is mainly based on the electromagnetic radiation emitted or reflected by the targets of interest and such signals are acquired by expensive sensors mounted on transportation platforms, e.g., satellites and aircrafts, which are not widely accessible. With the recent rapid advancement of technologies, many relatively more lightweight and sophisticated but yet more affordable sensors are developed. This coupled with increasingly more accessible new platforms, e.g., unmanned aerial vehicles, and high performance computing facilities have enabled more remotely sensed data, and in many applications various modalities of such data, to be acquired and processed to assist in delivering better decisions for each of these remote sensing applications.

The challenges imposed by the emerging interest and need for multimodal signal processing in remote sensing are in all its key stages, i.e., acquisition, processing, extraction and interpretation/analysis of multimodal and multi-temporal data. The modalities of interest include 2D optical images, 3D optical images (e.g., RGB, multispectral and hyperspectral data) and 3D unstructured point-cloud data (e.g., LiDAR).

This Special Issue will include high-quality research papers, work in progress papers, surveys, real-world application/deployment studies that discuss the theories and applications of addressing these challenges. Potential topics of interest for this Special Issue (but are not limited to) are:

• Design, calibration and setup of multimodal remote sensing systems
• Multimodal data processing, including techniques on segmentation, reconstruction, restoration, fusion, and registration
• Multimodal image classification
• Machine learning (including deep learning, multitask learning, and transfer learning) for multimodal remotely sensed data
• Novel benchmark multisource datasets
• Emerging applications on multimodal remote sensing

Dr. Shyh Wei Teng
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 250 words) can be sent to the Editorial Office for assessment.

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.