Special Session Scope

Hyperspectral imaging (HSI), also referred to as imaging spectroscopy, integrates conventional imaging and spectroscopy methods to obtain both spatial and spectral information of a scene.  Unlike conventional RGB (red, green and blue) image, which only captures three diffuse Gaussian spectral bands in the visible spectrum (e.g., 380 – 740 nm), HSI increases the amount of data acquired beyond the capabilities of the human eye. Hyperspectral (HS) sensors measure the aggregate signal of reflected, absorbed and emitted radiance at specific wavelengths of the material that is being observed. These sensors are capable of capturing a very large number of contiguous spectral bands (also called spectral wavelengths or spectral channels) across the electromagnetic spectrum, obtaining a vector of radiance values for each pixel of the image that is commonly called spectral signature. Image processing algorithms make use of these spectral signatures to automatically differentiate the materials observed by the sensor at each pixel. These methods rely on the basis that different molecular compositions of each material present in the nature has different responses to the incident light.

HSI is a promising non-invasive and non-ionizing technique that supports rapid acquisition and analysis of diagnostic information in several fields, such as remote sensing, archeology, drug identification, forensics, defense and security, agriculture, food safety inspection and control, among many others. However, in general, the algorithms to process such types of images have high computational requirements to achieve real-time processing, being necessary in many cases to employ high performance computing platforms.

In this Special Session the following topics of interest are included, but not limited to:

  • Algorithms and methods for HS data processing.
  • Systems and architectures for real-time HS data processing.
  • Different applications of HSI (health, smart farming, remote sensing, food quality, archeology, etc.).
  • Artificial intelligence methods for HS data processing.
  • Low-power implementations of HS architectures.
  • Sensors and systems for efficient HS data acquisition and processing.

Submission Guidelines

Authors are encouraged to submit their manuscripts via EasyChair web service at web page. Each manuscript should include the complete paper text, all illustrations, and references. The manuscript should conform to the IEEE format: single-spaced, double column, US letter page size, 10-point size Times Roman font, up to 8 pages. In order to conduct a blind review, no indication of the authors’ names should appear in the manuscript, references included.

Special Session Chair

Gustavo M. Callico (IUMA/ULPGC, ES)


Samuel Ortega (NOFIMA, NO)

Special Session Program Committee

  • Alejandro Cruz, Universidad Autonoma de San Luis Potosi, Mexico
  • Alfonso Rodríguez, Universidad Politécnica de Madrid, Spain
  • Antonio Núñez, University of Las Palmas de Gran Canaria, Spain
  • Antonio Sánchez-Clemente, University of Las Palmas de Gran Canaria, Spain
  • Caifeng Shan, Philips Research, The Netherlands
  • Claire Chalopin, Innovation Center Computer Assisted Surgery, University of Leipzig, Germany
  • Daniel Madroñal, Università degli Studi di Sassari, Italy
  • Daniel Ulises Campos-Delgado, Universidad Autonoma de San Luis Potosi, Mexico
  • Eduardo de la Torre, Universidad Politécnica de Madrid, Spain
  • Eduardo Juárez, Universidad Politécnica de Madrid, Spain
  • Eduardo Quevedo, University of Las Palmas de Gran Canaria, Spain
  • Emanuale Torti, University of Pavia, Italy
  • Francesca Manni, Eindhoven University of Technology, The Netherlands
  • Francesco Leporati, University of Pavia, Italy
  • Jesús Barba, University of Castilla-La Mancha, Spain
  • Lucana Santos, European Space Agency, The Netherlands
  • Marco La Salvia, University of Pavia, Italy
  • Marianne Maktabi, Universität Leipzig, Germany
  • Maysam Shahedi, The University of Texas at Dallas, USA
  • Miguel Chavarrías, Universidad Politécnica de Madrid, Spain
  • Raquel Lazcano, Università degli Studi di Sassari, Italy
  • Raquel León, University of Las Palmas de Gran Canaria, Spain
  • Svitlana Zinger, Eindhoven University of Technology, The Netherlands
  • Yúbal Barrios, University of Las Palmas de Gran Canaria, Spain

Contact Information

Gustavo M. Callico (IUMA/ULPGC, ES)

e-mail: gustavo@iuma.ulpgc.es


e-mail: hfabelo@iuma.ulpgc.es

Samuel Ortega (NOFIMA, NO)

e-mail: sortega@iuma.ulpgc.es