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Multimodal hyperspectral remote sensing: an overview and perspective

  • School of Electronics and Information Engineering, Harbin Institute of Technology
  • Heilongjiang Province Key Laboratory of Space-Air-Ground Integrated Intelligent Remote Sensing
  • Ministry of Natural Resources of the People's Republic of China
  • Grenoble Institute of Technology
  • University of New South Wales

Research output: Contribution to journalReview articlepeer-review

Abstract

Since the advent of hyperspectral remote sensing in the 1980s, it has made important achievements in aerospace and aviation field and been applied in many fields. Conventional hyperspectral imaging spectrometer extends the number of spectral bands to dozens or hundreds, and provides spatial distribution of the reflected solar radiation from the scene of observation at the same time. Nowadays, with the fast development of new technology in the fields of information and photoelectricity sensing, and the popularity of unmanned aerial vehicle, hyperspectral remote sensing imaging presents the new trends of multimodality and acquires integration information while keeping high or very-high spectral resolution, especially, high temporal even real time sensing and stereo sensing. Therefore, three important modes of hyperspectral imaging come into existence: (1) multitemporal hyperspectral imaging, which refers to the observation of same region at different dates; (2) hyperspectral video imaging, which captures full frame spectral images in real-time; (3) hyperspectral stereo imaging, which obtains the full dimension information (including 2D image, elevation, and spectra) of observed scene. Along this perspective, firstly, the current researches on hyperspectral remote sensing and image processing are briefly reviewed, and then, comprehensive descriptions of the aforementioned three main hyperspectral imaging modes are carried out from the following four aspects: fundamental principle of new mode of hyperspectral imaging, corresponding scientific data acquisition, data processing and application, and potential challenges in data representation, feature learning and interpretation. Through the analysis of development trend of hyperspectral imaging and current research situation, we hope to provide a direction for future research on multimodal hyperspectral remote sensing.

Original languageEnglish
Article number121301
JournalScience China Information Sciences
Volume64
Issue number2
DOIs
StatePublished - Feb 2021
Externally publishedYes

Keywords

  • hyperspectral image processing
  • hyperspectral stereo imaging
  • hyperspectral video imaging
  • multimodal hyperspectral remote sensing imaging
  • multitemporal hyperspectral imaging

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