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Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

651
Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
The ATR process begins by directing a beam...
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Related Experiment Video

Updated: Oct 18, 2025

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
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Recent Advances in Multi- and Hyperspectral Image Analysis.

Jakub Nalepa1

  • 1Department of Algorithmics and Software, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland.

Sensors (Basel, Switzerland)
|September 28, 2021
PubMed
Summary

Advancements in multi- and hyperspectral imaging offer new applications across many fields. Efficient processing pipelines are key for deploying this high-dimensional data, even in resource-limited environments like satellites.

Keywords:
classificationdimensionality reductionfeature extractionhyperspectral image analysisimage acquisitionmultispectral image analysissegmentationunmixing

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Area of Science:

  • Remote Sensing
  • Image Processing
  • Machine Learning

Background:

  • Sensor technology advancements enable new possibilities in multi- and hyperspectral imaging.
  • Applications span precision agriculture, medicine, land cover analysis, and disaster detection.

Discussion:

  • High-dimensional data from hundreds of spectral bands requires efficient processing.
  • Developing advanced image processing and machine learning pipelines is crucial.

Key Insights:

  • Multi- and hyperspectral analysis is a rapidly growing research area.
  • Efficient algorithms facilitate practical adoption of this technology.

Outlook:

  • Enables faster adoption of hyperspectral imaging in various domains.
  • Facilitates deployment in hardware-constrained environments, such as on-board satellites.