Advances in Hyperspectral Remote Sensing: Methods and Applications II

This is the second Special Issue concerning the contributions of Advances in Hyperspectral Remote Sensing: Methods and Applications. (https://0-www-mdpi-com.brum.beds.ac.uk/journal/remotesensing/special_issues/rs_hyperspectral)

Benefiting from the development of hyperspectral satellites, hyperspectral imaging has played an important role in remote sensing. Hyperspectral images collect information with contiguous or noncontiguous 10 nm bands across the 400–2500 nm region of the electromagnetic spectrum. Thus, hyperspectral images with hundreds of spectral bands including abundant spectral information can be applied for the detection of minerals, environmental monitoring, and defense.

By combining imaging and spectroscopy in a system, hyperspectral images always have complex high-dimensional data structures, leading to the difficulty in processing and analyzing hyperspectral images with high efficiency. For example, the ill-posed problem in the recovery of high-dimensional data is more challenging than that of low-dimensional data. Although numerous efforts have been devoted to addressing special hyperspectral remote sensing tasks, complex datasets in real applications and difficult real-world tasks still put forward urgent requirements of advanced hyperspectral remote sensing methods. Further, the applications of hyperspectral remote sensing have been hot topics in recent years.

This Special Issue aims to gather high-level contributions related to advances in hyperspectral remote sensing. Both original research articles with innovative ideas and review articles discussing the state of the art are welcomed. Specific topics of interest include, but are not limited to, the following:

Hyperspectral image denoising, deblurring, unmixing, and restoration; image super-resolution, image fusion, and image segmentation; image quality assessment; classification, clustering, and object detection; deep learning technique in hyperspectral image processing; registration and feature selection; model-based approaches and tensor decomposition; change detection and compression; surveys of recent progress; and application of hyperspectral remote sensing.

Prof. Dr. Jiayi Ma
Prof. Dr. Xin Tian
Prof. Dr. Jun Chen
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. 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.

• remote sensing
• hyperspectral image
• hyperspectral image denoise
• hyperspectral image unmixing
• hyperspectral image super-resolution
• hyperspectral image fusion
• hyperspectral image classification
• image registration
• change detection

• Advances in Hyperspectral Remote Sensing: Methods and Applications in Remote Sensing (11 articles)