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How Good Are RGB Cameras Retrieving Colors of Natural Scenes and Paintings?—A Study Based on Hyperspectral Imaging
RGB digital cameras (RGB) compress the spectral information into a trichromatic system capable of approximately representing the actual colors of objects. Although RGB digital cameras follow the same compression philosophy as the human eye (OBS), the spectral sensitivity is different. To what extent...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663052/ https://www.ncbi.nlm.nih.gov/pubmed/33139611 http://dx.doi.org/10.3390/s20216242 |
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author | Linhares, João M. M. Monteiro, José A. R. Bailão, Ana Cardeira, Liliana Kondo, Taisei Nakauchi, Shigeki Picollo, Marcello Cucci, Costanza Casini, Andrea Stefani, Lorenzo Nascimento, Sérgio Miguel Cardoso |
author_facet | Linhares, João M. M. Monteiro, José A. R. Bailão, Ana Cardeira, Liliana Kondo, Taisei Nakauchi, Shigeki Picollo, Marcello Cucci, Costanza Casini, Andrea Stefani, Lorenzo Nascimento, Sérgio Miguel Cardoso |
author_sort | Linhares, João M. M. |
collection | PubMed |
description | RGB digital cameras (RGB) compress the spectral information into a trichromatic system capable of approximately representing the actual colors of objects. Although RGB digital cameras follow the same compression philosophy as the human eye (OBS), the spectral sensitivity is different. To what extent they provide the same chromatic experiences is still an open question, especially with complex images. We addressed this question by comparing the actual colors derived from spectral imaging with those obtained with RGB cameras. The data from hyperspectral imaging of 50 natural scenes and 89 paintings was used to estimate the chromatic differences between OBS and RGB. The corresponding color errors were estimated and analyzed in the color spaces CIELAB (using the color difference formulas ΔE(*)(ab) and CIEDE2000), J(z)a(z)b(z), and iCAM06. In CIELAB the most frequent error (using ΔE(*)(ab)) found was 5 for both paintings and natural scenes, a similarity that held for the other spaces tested. In addition, the distribution of errors across the color space shows that the errors are small in the achromatic region and increase with saturation. Overall, the results indicate that the chromatic errors estimated are close to the acceptance error and therefore RGB digital cameras are able to produce quite realistic colors of complex scenarios. |
format | Online Article Text |
id | pubmed-7663052 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76630522020-11-14 How Good Are RGB Cameras Retrieving Colors of Natural Scenes and Paintings?—A Study Based on Hyperspectral Imaging Linhares, João M. M. Monteiro, José A. R. Bailão, Ana Cardeira, Liliana Kondo, Taisei Nakauchi, Shigeki Picollo, Marcello Cucci, Costanza Casini, Andrea Stefani, Lorenzo Nascimento, Sérgio Miguel Cardoso Sensors (Basel) Article RGB digital cameras (RGB) compress the spectral information into a trichromatic system capable of approximately representing the actual colors of objects. Although RGB digital cameras follow the same compression philosophy as the human eye (OBS), the spectral sensitivity is different. To what extent they provide the same chromatic experiences is still an open question, especially with complex images. We addressed this question by comparing the actual colors derived from spectral imaging with those obtained with RGB cameras. The data from hyperspectral imaging of 50 natural scenes and 89 paintings was used to estimate the chromatic differences between OBS and RGB. The corresponding color errors were estimated and analyzed in the color spaces CIELAB (using the color difference formulas ΔE(*)(ab) and CIEDE2000), J(z)a(z)b(z), and iCAM06. In CIELAB the most frequent error (using ΔE(*)(ab)) found was 5 for both paintings and natural scenes, a similarity that held for the other spaces tested. In addition, the distribution of errors across the color space shows that the errors are small in the achromatic region and increase with saturation. Overall, the results indicate that the chromatic errors estimated are close to the acceptance error and therefore RGB digital cameras are able to produce quite realistic colors of complex scenarios. MDPI 2020-11-01 /pmc/articles/PMC7663052/ /pubmed/33139611 http://dx.doi.org/10.3390/s20216242 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Linhares, João M. M. Monteiro, José A. R. Bailão, Ana Cardeira, Liliana Kondo, Taisei Nakauchi, Shigeki Picollo, Marcello Cucci, Costanza Casini, Andrea Stefani, Lorenzo Nascimento, Sérgio Miguel Cardoso How Good Are RGB Cameras Retrieving Colors of Natural Scenes and Paintings?—A Study Based on Hyperspectral Imaging |
title | How Good Are RGB Cameras Retrieving Colors of Natural Scenes and Paintings?—A Study Based on Hyperspectral Imaging |
title_full | How Good Are RGB Cameras Retrieving Colors of Natural Scenes and Paintings?—A Study Based on Hyperspectral Imaging |
title_fullStr | How Good Are RGB Cameras Retrieving Colors of Natural Scenes and Paintings?—A Study Based on Hyperspectral Imaging |
title_full_unstemmed | How Good Are RGB Cameras Retrieving Colors of Natural Scenes and Paintings?—A Study Based on Hyperspectral Imaging |
title_short | How Good Are RGB Cameras Retrieving Colors of Natural Scenes and Paintings?—A Study Based on Hyperspectral Imaging |
title_sort | how good are rgb cameras retrieving colors of natural scenes and paintings?—a study based on hyperspectral imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663052/ https://www.ncbi.nlm.nih.gov/pubmed/33139611 http://dx.doi.org/10.3390/s20216242 |
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