Special Issue "The Future of Hyperspectral Imaging"

A special issue of Journal of Imaging (ISSN 2313-433X).

Deadline for manuscript submissions: closed (26 October 2018)

Special Issue Editor

Guest Editor
Dr. Stefano Selci

IFN-CNR, 00133 Roma, Italy
Website | E-Mail
Interests: spectroscopy; scanning microscopy; hyperspectral imaging

Special Issue Information

Dear Colleagues,

Hyperspectral-based techniques (HSI) are pervading many, and increasing, fields of application. HSI began as a quite obvious tool within remote airborne observations; for instance, to determine land resources. The rapid development of spectroscopic hardware allowed fundamental passage of HSI from multispectral analyses (a few spectral lines), up to the full control and capture of spectral continuous ranges, while expanding its realm to food, biology, medicine, forensics, and art observation, just to name a few. The remarkable mix of the information (often represented as “hypercubes”) is at the same time spectroscopic (wavelength axis), structural (three axes), and plus time (a further axis). The structural part represents a range of information that can be within at least six orders of magnitude between micrometers (using HSI methods within microscopes, also of confocal type) and meters, while the usually-available large spectral range can be further functionally increased by adding fluorescence and Raman spectroscopies.

However, the rapid increase in the application areas will require a much higher speed in acquisition, clever data elaboration (e.g., neural networking methods are already used to safely assign local spectroscopic fingerprints to HIS images ), new hardware, and new ideas. There is a need to have effective tools, for instance, to make food analyses on real stocks, in real time and compatible with the daily products’ market, or make diagnoses on cells to reveal cancer during a routine medical check, without the need for a long wait.

Which advancements will be eventually more productive and innovative in this field?

We request contributions presenting techniques (methods, tools, ideas, or even market evaluations) that will contribute to the future roadmap of HSI, as well as concepts for significantly innovative objectives in HSI techniques.  Scientifically founded innovative and speculative research lines are welcome for proposal and evaluation.

Dr. Stefano Selci
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 papers will be 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. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) is waived for well-prepared manuscripts submitted to this issue. 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

  • Hyperspectral imaging
  • Real time imaging and spectroscopies
  • Medical imaging by HSI
  • HSI for biology
  • Remote sensing
  • Hyperspectral microscopy
  • Fluorescence hyperspectral imaging
  • Raman hyperspectral imaging
  • Infrared hyperspectral imaging
  • Nanoscale imaging in HSI
  • Statistical methods for HSI
  • Hyperspectral data mining and compression
  • Hardware solutions for compact HSI instrumentation
  • Hyperspectral market forecast

Published Papers (2 papers)

View options order results:
result details:
Displaying articles 1-2
Export citation of selected articles as:

Research

Open AccessArticle Fusing Multiple Multiband Images
J. Imaging 2018, 4(10), 118; https://doi.org/10.3390/jimaging4100118
Received: 21 August 2018 / Revised: 5 October 2018 / Accepted: 8 October 2018 / Published: 12 October 2018
PDF Full-text (4646 KB) | HTML Full-text | XML Full-text
Abstract
High-resolution hyperspectral images are in great demand but hard to acquire due to several existing fundamental and technical limitations. A practical way around this is to fuse multiple multiband images of the same scene with complementary spatial and spectral resolutions. We propose an
[...] Read more.
High-resolution hyperspectral images are in great demand but hard to acquire due to several existing fundamental and technical limitations. A practical way around this is to fuse multiple multiband images of the same scene with complementary spatial and spectral resolutions. We propose an algorithm for fusing an arbitrary number of coregistered multiband, i.e., panchromatic, multispectral, or hyperspectral, images through estimating the endmember and their abundances in the fused image. To this end, we use the forward observation and linear mixture models and formulate an appropriate maximum-likelihood estimation problem. Then, we regularize the problem via a vector total-variation penalty and the non-negativity/sum-to-one constraints on the endmember abundances and solve it using the alternating direction method of multipliers. The regularization facilitates exploiting the prior knowledge that natural images are mostly composed of piecewise smooth regions with limited abrupt changes, i.e., edges, as well as coping with potential ill-posedness of the fusion problem. Experiments with multiband images constructed from real-world hyperspectral images reveal the superior performance of the proposed algorithm in comparison with the state-of-the-art algorithms, which need to be used in tandem to fuse more than two multiband images. Full article
(This article belongs to the Special Issue The Future of Hyperspectral Imaging)
Figures

Figure 1

Open AccessArticle Hyperspectral Imaging Using Laser Excitation for Fast Raman and Fluorescence Hyperspectral Imaging for Sorting and Quality Control Applications
J. Imaging 2018, 4(10), 110; https://doi.org/10.3390/jimaging4100110
Received: 24 August 2018 / Revised: 14 September 2018 / Accepted: 19 September 2018 / Published: 21 September 2018
PDF Full-text (3041 KB) | HTML Full-text | XML Full-text
Abstract
A hyperspectral measurement system for the fast and large area measurement of Raman and fluorescence signals was developed, characterized and tested. This laser hyperspectral imaging system (Laser-HSI) can be used for sorting tasks and for continuous quality monitoring. The system uses a 532
[...] Read more.
A hyperspectral measurement system for the fast and large area measurement of Raman and fluorescence signals was developed, characterized and tested. This laser hyperspectral imaging system (Laser-HSI) can be used for sorting tasks and for continuous quality monitoring. The system uses a 532 nm Nd:YAG laser and a standard pushbroom HSI camera. Depending on the lens selected, it is possible to cover large areas (e.g., field of view (FOV) = 386 mm) or to achieve high spatial resolutions (e.g., 0.02 mm). The developed Laser-HSI was used for four exemplary experiments: (a) the measurement and classification of a mixture of sulphur and naphthalene; (b) the measurement of carotenoid distribution in a carrot slice; (c) the classification of black polymer particles; and, (d) the localization of impurities on a lead zirconate titanate (PZT) piezoelectric actuator. It could be shown that the measurement data obtained were in good agreement with reference measurements taken with a high-resolution Raman microscope. Furthermore, the suitability of the measurements for classification using machine learning algorithms was also demonstrated. The developed Laser-HSI could be used in the future for complex quality control or sorting tasks where conventional HSI systems fail. Full article
(This article belongs to the Special Issue The Future of Hyperspectral Imaging)
Figures

Graphical abstract

Back to Top