Emerging Technologies in Hyperspectral Image 3A—Acquisition, Analysis and Application
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 January 2026 | Viewed by 496
Special Issue Editors
Interests: signal and Image processing; machine learning
Interests: hyperspectral image processing; image denoising; image demosaicking; image compression
Interests: hyperspectral image processing; deep learning; image enhancement; inverse problem
Interests: spectral unmixing; multimodal image fusion; image reconstruction; image generation; probabilistic machine learning
Special Issue Information
Dear Colleagues,
Hyperspectral imaging has revolutionized remote sensing by enabling the capture of high-resolution spectral information across up to thousands of bands, offering unprecedented insights into Earth's surface composition and dynamics. This technology enables precise analysis of materials and features based on their spectral signatures. With the commercialization of underwater, field-portable, airborne, and spaceborne hyperspectral imaging devices, hyperspectral data has been indispensable in a wide range of applications, from smart agriculture and urban planning to resource exploration and meteorology. As the demand for detailed and accurate spectral information continues to grow, advancements in hyperspectral image acquisition, analysis, and application have become increasingly pivotal in addressing complex scientific and practical challenges.
This special issue aims to showcase the latest advancements and innovations in hyperspectral imaging technology, highlighting cutting-edge research that enhances our understanding of hyperspectral data acquisition, analysis, and application across various domains. It encourages contributions that explore new methodologies, algorithms, and practical engineering in the remote sensing community.
We invite original research articles, reviews, technical notes and communication papers. Suggested themes include but are not limited to the following topics:
- Acquisition techniques and computational imaging for hyperspectral remote sensing (e.g., demosaicking, denoising, deconvolution, pansharpening, super-resolution, compression);
- Analysis and calibration for hyperspectral remote sensing (e.g., feature extraction, clustering, unmixing, image fusion, image registration, dimensionality reduction, band selection);
- Application of hyperspectral remote sensing (e.g., water/ocean observation, underwater imaging, vegetation monitoring, oil and mineral exploration, atmospheric composition tracking);
- Review of hyperspectral image processing methods;
- Research directions, opportunities and open challenges in hyperspectral remote sensing in the deep learning era.
Prof. Dr. Jie Chen
Dr. Shumin Liu
Dr. Min Zhao
Dr. Shuaikai Shi
Dr. Xiuheng Wang
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 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.
Keywords
- image processing
- hyperspectral data acquisition
- computational imaging
- spectral and spatial analysis
- AI-tools
- hyperspectral applications
- deep learning
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