IEEE Access· 2018Q1· Review
Modern Trends in Hyperspectral Image Analysis: A Review
- 857citations
- Q1SCImago
- 2018year
Short summary
Hyperspectral imaging, enabled by advanced sensors, is increasingly used across civil, environmental, and military fields for detailed surface analysis and material identification, with recent focus on ground-based applications in food, medicine, and forensics.
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Key points
- Hyperspectral imaging offers exceptional spatial, spectral, and temporal resolutions for detailed surface analysis.
- Applications span remote sensing, food quality, medical diagnosis, forensic science, and defense.
- Ground-based hyperspectral imaging is gaining traction in fields like food inspection and medical surgery.
- Deep learning is being integrated for advanced tasks like forgery detection in questioned documents.
AI-generated from the title and abstract; the full text is not read.
Abstract
Over the past three decades, significant developments have been made in hyperspectral imaging due to which it has emerged as an effective tool in numerous civil, environmental, and military applications. Modern sensor technologies are capable of covering large surfaces of earth with exceptional spatial, spectral, and temporal resolutions. Due to these features, hyperspectral imaging has been effectively used in numerous remote sensing applications requiring estimation of physical parameters of many complex surfaces and identification of visually similar materials having fine spectral signatures. In the recent years, ground based hyperspectral imaging has gained immense interest in the research on electronic imaging for food inspection, forensic science, medical surgery and diagnosis, and military applications. This review focuses on the fundamentals of hyperspectral image analysis and its modern applications such as food quality and safety assessment, medical diagnosis and image guided surgery, forensic document examination, defense and homeland security, remote sensing applications such as precision agriculture and water resource management and material identification and mapping of artworks. Moreover, recent research on the use of hyperspectral imaging for examination of forgery detection in questioned documents, aided by deep learning, is also presented. This review can be a useful baseline for future research in hyperspectral image analysis.
The authors' abstract, as published at the source. IEEE Access, 2018 · DOI ↗
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Field: Analytical Chemistry
Analytical ChemistryChemistry