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Advanced Technologies and Applications of Hyperspectral Images

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (15 October 2023) | Viewed by 457

Special Issue Editors


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Guest Editor
College of Information Science and Technology, Donghua University, Shanghai, China
Interests: image processing and pattern recognition; hyperspectral data analysis and processing; multi-source information fusion and application

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Guest Editor
Department of Embedded Systems Engineering, Incheon National University, 119 Academy-ro, Yeonsu-gu, Incheon 22012, Republic of Korea
Interests: remote sensing; deep learning; artificial intelligence; image processing; signal processing
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Special Issue Information

Dear Colleagues,

Within the past several decades, owing to the improvement of the ability and performance of imaging sensors, spectral imaging technology has significantly enhanced observation abilities in various areas. By providing the spectral information and spatial structure features of objects simultaneously, hyperspectral imagery has proved to be a more effective technique for land-cover classification and ground-object detection than conventional single- and multi-band images. However, hyperspectral imagery suffers from a series of problems in practice, such as high dimensions, data redundancy, spectral mixing, etc. This has inspired a great deal of valuable hyperspectral image-related research. This Special Issue aims to support the development and collection of new proposals about hyperspectral image processing and applications. We welcome contributions in all fields of hyperspectral imagery, including sensor technology, imaging systems, image-processing algorithms, applications, as well as the summarization of developments in hyperspectral imagery. The topics include, but are not limited to:

  • Hyperspectral imaging systems;
  • Hyperspectral data feature extraction;
  • Hyperspectral unmixing and super-resolution;
  • Hyperspectral image classification;
  • Data fusion of hyperspectral and other data types;
  • Target detection and recognition;
  • Machine-learning-based techniques;
  • Hyperspectral image applications in agriculture, water pollution, etc.

Dr. Xiaochen Lu
Dr. Gwanggil Jeon
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. Sensors 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 2600 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.

Published Papers

There is no accepted submissions to this special issue at this moment.
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