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Related Concept Videos

UV–Vis Spectrometers01:14

UV–Vis Spectrometers

The absorbance of UV and visible (UV–visible) radiations is measured using a UV–visible spectrophotometer. Deuterium lamps, which emit UV radiation, and tungsten lamps, which produce radiation in the visible region, are used as light sources in UV–visible spectrophotometers. A monochromator or prism is used for diffraction grating, i.e., to split the incoming radiation into different wavelengths. A system of slits is used to focus the desired wavelength on the sample cell. Samples for...
UV–Vis Spectrum01:30

UV–Vis Spectrum

When light passes through a substance, a portion of the light is absorbed while the remaining light is reflected or transmitted. If the molecule absorbs light between the wavelengths of 180–400 nm range, the UV spectrum is obtained, and if it absorbs light in the 400–780 nm wavelength range, the visible spectrum is obtained.     
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IR Spectrum01:19

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When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
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Infrared (IR) Spectroscopy: Overview

When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
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Flame Photometry: Overview01:02

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Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
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Emission Spectra

When solids, liquids, or condensed gases are heated sufficiently, they radiate some of the excess energy as light. Photons produced in this manner have a range of energies, and thereby produce a continuous spectrum in which an unbroken series of wavelengths is present.

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ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
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Illuminant spectrum estimation at a pixel.

Sivalogeswaran Ratnasingam1, Javier Hernández-Andrés

  • 11Intelligent Systems Research Centre, School of Computing and Intelligent Systems, Magee Campus, University of Ulster, Londonderry, Northern Ireland, BT48 7JL, UK. s.ratnasingam@ulster.ac.uk

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|April 12, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces an algorithm to estimate light source spectral power distribution using a chromaticity space. Six sensors provide colorimetrically accurate illuminant spectrum estimates at each pixel.

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Area of Science:

  • Computer Vision
  • Color Science
  • Image Processing

Background:

  • Estimating the spectral power distribution of light sources is crucial for accurate color reproduction in digital imaging.
  • Existing methods often struggle with complex illumination conditions and sensor noise.

Purpose of the Study:

  • To develop and validate a novel algorithm for pixel-wise illuminant spectrum estimation.
  • To determine the optimal number of sensors for achieving accurate colorimetric and spectral reproduction.

Main Methods:

  • Formation of a two-dimensional illuminant invariant chromaticity space.
  • Application of generalized inverse and Wiener estimation methods for illuminant spectrum estimation.
  • Utilizing a weight matrix within a gridded chromaticity space to refine estimates.
  • Testing algorithm performance with varying sensor numbers, Gaussian noise, and 10-bit quantization.

Main Results:

  • The algorithm demonstrates the ability to estimate the spectral power distribution of light sources at a pixel level.
  • Performance evaluation indicates that six sensors are optimal for achieving colorimetrically accurate illuminant spectrum estimation.
  • The method shows robustness when subjected to noise and quantization.

Conclusions:

  • The proposed algorithm offers a reliable method for estimating illuminant spectra at the pixel level.
  • The use of six sensors is recommended for optimal colorimetric accuracy in spectral reproduction.
  • This technique has potential applications in digital photography, computer vision, and color management systems.