2021
DOI: 10.3390/s21186002
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Recent Advances in Multi- and Hyperspectral Image Analysis

Abstract: Current advancements in sensor technology bring new possibilities in multi- and hyperspectral imaging. Real-life use cases which can benefit from such imagery span across various domains, including precision agriculture, chemistry, biology, medicine, land cover applications, management of natural resources, detecting natural disasters, and more. To extract value from such highly dimensional data capturing up to hundreds of spectral bands in the electromagnetic spectrum, researchers have been developing a range… Show more

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Cited by 36 publications
(28 citation statements)
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“…Although first developed in the context of improving space exploration [ 42 ], HSI has been readily adapted to head and neck surgery. This methodology collects reflected light across a continuum of spectral bands, generating objective surface analysis data in a noninvasive, tracer-free process [ 43 ]. Halicek et al were among the first to utilize this imaging modality to determine cancer margins in ex vivo HNC specimens [ 5 , 44 , 45 ].…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Although first developed in the context of improving space exploration [ 42 ], HSI has been readily adapted to head and neck surgery. This methodology collects reflected light across a continuum of spectral bands, generating objective surface analysis data in a noninvasive, tracer-free process [ 43 ]. Halicek et al were among the first to utilize this imaging modality to determine cancer margins in ex vivo HNC specimens [ 5 , 44 , 45 ].…”
Section: Resultsmentioning
confidence: 99%
“…Hyperspectral imaging [5,[42][43][44][45][46] Makes use of extended spectral information from tissues, outside the limited range of RGB wavelengths. This allows for the generation of a 2D image with a corresponding 3D dataset on wavelengths (hyperspectral cube).…”
Section: Similar Weaknesses As Nbimentioning
confidence: 99%
“…As reported by [24][25][26], PLSR has become a popular multivariate statistical technique for improving predictions based on leaf optical properties [27]. PLSR has been shown to have a strong relationship with the prediction of photosynthetic pigment concentration, especially when combined with multispectral and hyperspectral data [5,28]. PLSR, when combined with remote sensing techniques that collect high-resolution data across various wavelengths [28,29], offers a powerful tool to understand the intricate relationships between plant physiology, environmental conditions, and the prediction of various biochemical and biophysical process parameters [5,23,30].…”
Section: Introductionmentioning
confidence: 99%
“…Current advancements in sensor technology bring new possibilities in multi-and hyperspectral images (MSI/HSI). Real-life use cases which can benefit from such imagery span across various domains, including precision agriculture [8], chemistry [9], biology, medicine [10], land cover applications [11,12], detecting natural disasters [13], and more [14]. To extract value from such highly dimensional data capturing up to hundreds of spectral bands in the electromagnetic spectrum, researchers have been developing a range of image processing and machine learning analysis pipelines to process the MSI/HSI data as efficiently as possible.…”
Section: Introduction and Objectivesmentioning
confidence: 99%